diff --git a/interactive_ai/libs/iai_core_py/iai_core/factories/project_validator.py b/interactive_ai/libs/iai_core_py/iai_core/factories/project_validator.py
index 712e43b27..25e2f9c48 100644
--- a/interactive_ai/libs/iai_core_py/iai_core/factories/project_validator.py
+++ b/interactive_ai/libs/iai_core_py/iai_core/factories/project_validator.py
@@ -146,6 +146,7 @@ def _validate_empty_labels(cls, parser: ParserT) -> None:
                     raise ReservedLabelNameException(label_name=empty_label_name)
 
     @classmethod
+    @abstractmethod
     def _validate_keypoint_structure(cls, parser: ParserT) -> None:
         """
         Validates that a user defined label graph edge has exactly 2 nodes, node names match with existing labels,
@@ -160,29 +161,6 @@ def _validate_keypoint_structure(cls, parser: ParserT) -> None:
         :raises NodeNameNotInLabelsException: if a node name does not match any of the label names
         :raises NodePositionIsOutOfBoundsException: if a node is out of bounds (not in the range [0.0, 1.0])
         """
-        duplicate_list = []
-        for task_name in parser.get_tasks_names():
-            keypoint_structure = parser.get_keypoint_structure_data(task_name=task_name)
-            if not keypoint_structure:
-                continue
-            label_names = parser.get_custom_labels_names_by_task(task_name=task_name)
-            edges = keypoint_structure["edges"]
-            for edge in edges:
-                nodes = edge["nodes"]
-                if len(nodes) != 2:
-                    raise WrongNumberOfNodesException
-                if nodes[0] not in label_names or nodes[1] not in label_names:
-                    raise IncorrectNodeNameInGraphException
-                if set(nodes) in duplicate_list:
-                    raise DuplicateEdgeInGraphException
-                duplicate_list.append(set(nodes))
-
-            positions = keypoint_structure["positions"]
-            for position in positions:
-                if position["label"] not in label_names:
-                    raise NodeNameNotInLabelsException
-                if not 0 <= position["x"] <= 1 or not 0 <= position["y"] <= 1:
-                    raise NodePositionIsOutOfBoundsException
 
     @classmethod
     @abstractmethod
@@ -417,6 +395,45 @@ def __validate_parent_labels_in_parent_task(
                     ),
                 )
 
+    @classmethod
+    def _validate_keypoint_structure(cls, parser: ProjectParser) -> None:
+        """
+        Validates that a user defined label graph edge has exactly 2 nodes, node names match with existing labels,
+        and has no duplicate edges
+
+        This method must be run after labels validation since it assumes that its labels param is valid.
+
+        :param parser: A parser instance that can read and decode the information necessary to create a project
+        :raises WrongNumberOfNodesException: if an edge does not have 2 vertices
+        :raises IncorrectNodeNameInGraphException: if an edge has an incorrect name
+        :raises DuplicateEdgeInGraphException: if the graph contains a duplicate edge
+        :raises NodeNameNotInLabelsException: if a node name does not match any of the label names
+        :raises NodePositionIsOutOfBoundsException: if a node is out of bounds (not in the range [0.0, 1.0])
+        """
+        duplicate_list = []
+        for task_name in parser.get_tasks_names():
+            keypoint_structure = parser.get_keypoint_structure_data(task_name=task_name)
+            if not keypoint_structure:
+                continue
+            label_names = parser.get_custom_labels_names_by_task(task_name=task_name)
+            edges = keypoint_structure["edges"]
+            for edge in edges:
+                nodes = edge["nodes"]
+                if len(nodes) != 2:
+                    raise WrongNumberOfNodesException
+                if nodes[0] not in label_names or nodes[1] not in label_names:
+                    raise IncorrectNodeNameInGraphException
+                if set(nodes) in duplicate_list:
+                    raise DuplicateEdgeInGraphException
+                duplicate_list.append(set(nodes))
+
+            positions = keypoint_structure["positions"]
+            for position in positions:
+                if position["label"] not in label_names:
+                    raise NodeNameNotInLabelsException
+                if not 0 <= position["x"] <= 1 or not 0 <= position["y"] <= 1:
+                    raise NodePositionIsOutOfBoundsException
+
 
 class ProjectUpdateValidator(ProjectValidator[ProjectUpdateParser]):
     def validate(self, parser: ProjectUpdateParser) -> None:
@@ -726,3 +743,47 @@ def __validate_parent_labels_in_parent_task(
                         if not is_found
                     ),
                 )
+
+    @classmethod
+    def _validate_keypoint_structure(cls, parser: ProjectUpdateParser) -> None:
+        """
+        Validates that a user defined label graph edge has exactly 2 nodes, node names match with existing labels,
+        and has no duplicate edges
+
+        This method must be run after labels validation since it assumes that its labels param is valid.
+
+        :param parser: A parser instance that can read and decode the information necessary to create a project
+        :raises WrongNumberOfNodesException: if an edge does not have 2 vertices
+        :raises IncorrectNodeNameInGraphException: if an edge has an incorrect name
+        :raises DuplicateEdgeInGraphException: if the graph contains a duplicate edge
+        :raises NodeNameNotInLabelsException: if a node name does not match any of the label names
+        :raises NodePositionIsOutOfBoundsException: if a node is out of bounds (not in the range [0.0, 1.0])
+        """
+        duplicate_list = []
+        for task_name in parser.get_tasks_names():
+            keypoint_structure = parser.get_keypoint_structure_data(task_name=task_name)
+            if not keypoint_structure:
+                continue
+            label_names = list(parser.get_custom_labels_names_by_task(task_name=task_name))
+            label_ids = [
+                str(parser.get_label_id_by_name(task_name=task_name, label_name=label_name))
+                for label_name in label_names
+            ]
+            labels = label_names + label_ids
+            edges = keypoint_structure["edges"]
+            for edge in edges:
+                nodes = edge["nodes"]
+                if len(nodes) != 2:
+                    raise WrongNumberOfNodesException
+                if nodes[0] not in labels or nodes[1] not in labels:
+                    raise IncorrectNodeNameInGraphException
+                if set(nodes) in duplicate_list:
+                    raise DuplicateEdgeInGraphException
+                duplicate_list.append(set(nodes))
+
+            positions = keypoint_structure["positions"]
+            for position in positions:
+                if position["label"] not in labels:
+                    raise NodeNameNotInLabelsException
+                if not 0 <= position["x"] <= 1 or not 0 <= position["y"] <= 1:
+                    raise NodePositionIsOutOfBoundsException
diff --git a/interactive_ai/libs/iai_core_py/iai_core/utils/project_builder.py b/interactive_ai/libs/iai_core_py/iai_core/utils/project_builder.py
index b1c3304d3..737250ae2 100644
--- a/interactive_ai/libs/iai_core_py/iai_core/utils/project_builder.py
+++ b/interactive_ai/libs/iai_core_py/iai_core/utils/project_builder.py
@@ -827,15 +827,16 @@ def _build_keypoint_structure(
         :return: the KeypointStructure
         """
         label_name_to_id: dict[str, ID] = {label.name: label.id_ for label in labels}
+        label_ids = [label.id_ for label in labels]
         edges = []
         for edge in keypoint_structure_data["edges"]:
-            node_1 = label_name_to_id[edge["nodes"][0]]
-            node_2 = label_name_to_id[edge["nodes"][1]]
+            node_1 = ID(edge["nodes"][0]) if ID(edge["nodes"][0]) in label_ids else label_name_to_id[edge["nodes"][0]]
+            node_2 = ID(edge["nodes"][1]) if ID(edge["nodes"][1]) in label_ids else label_name_to_id[edge["nodes"][1]]
             edges.append(KeypointEdge(node_1=node_1, node_2=node_2))
 
         positions = []
         for position in keypoint_structure_data["positions"]:
-            node = label_name_to_id[position["label"]]
+            node = ID(position["label"]) if ID(position["label"]) in label_ids else label_name_to_id[position["label"]]
             x = position["x"]
             y = position["y"]
             positions.append(KeypointPosition(node=node, x=x, y=y))
diff --git a/interactive_ai/libs/iai_core_py/iai_core/utils/project_factory.py b/interactive_ai/libs/iai_core_py/iai_core/utils/project_factory.py
index 47dd8caae..687b780e8 100644
--- a/interactive_ai/libs/iai_core_py/iai_core/utils/project_factory.py
+++ b/interactive_ai/libs/iai_core_py/iai_core/utils/project_factory.py
@@ -22,7 +22,7 @@
 from iai_core.entities.model_template import ModelTemplate, NullModelTemplate
 from iai_core.entities.project import Project
 from iai_core.entities.task_graph import TaskEdge, TaskGraph
-from iai_core.entities.task_node import TaskNode, TaskProperties
+from iai_core.entities.task_node import TaskNode, TaskProperties, TaskType
 from iai_core.repos import (
     ActiveModelStateRepo,
     ConfigurableParametersRepo,
@@ -109,6 +109,7 @@ def create_project_with_task_graph(  # noqa: PLR0913
         project_id: ID | None = None,
         user_names: list[str] | None = None,
         hidden: bool = False,
+        keypoint_structure: KeypointStructure | None = None,
     ) -> Project:
         """
         Create a project given a task graph
@@ -122,6 +123,7 @@ def create_project_with_task_graph(  # noqa: PLR0913
         :param model_templates: List of model templates to create the model storages for each task
         :param user_names: User names to assign to the project
         :param hidden: Whether to keep the project as hidden after creation
+        :param keypoint_structure: Keypoint structure to assign to the project, only for Keypoint Detection projects
         :return: created project
         """
         if project_id is None:
@@ -146,8 +148,8 @@ def create_project_with_task_graph(  # noqa: PLR0913
             _id=DatasetStorageRepo.generate_id(),
         )
         DatasetStorageRepo(project_identifier).save(dataset_storage)
-        keypoint_structure = None
-        if FeatureFlagProvider.is_enabled(FEATURE_FLAG_KEYPOINT_DETECTION):
+
+        if FeatureFlagProvider.is_enabled(FEATURE_FLAG_KEYPOINT_DETECTION) and keypoint_structure is None:
             keypoint_structure = KeypointStructure(
                 edges=[KeypointEdge(node_1=ID("node_1"), node_2=ID("node_2"))],
                 positions=[
@@ -155,6 +157,7 @@ def create_project_with_task_graph(  # noqa: PLR0913
                     KeypointPosition(node=ID("node_2"), x=1, y=1),
                 ],
             )
+
         # Create graph with one task
         project = Project(
             id=project_id,
@@ -252,6 +255,7 @@ def create_project_single_task(  # noqa: PLR0915, PLR0913
         empty_label_name: str | None = None,
         is_multi_label_classification: bool | None = False,
         hidden: bool = False,
+        keypoint_structure: KeypointStructure | None = None,
     ) -> Project:
         """
         Create a project with one task in the pipeline.
@@ -267,19 +271,19 @@ def create_project_single_task(  # noqa: PLR0915, PLR0913
             This attribute is ignored when label_schema is provided.
         :param model_template_id: Model template for the project
             (either the model template ID or the model template itself)
-        :param user_names: User names to assign to the project
-        :param configurable_parameters: Optional, configurable parameters to assign
-            to the task node in the Project.
-        :param workspace: Optional, workspace
+        :param user_names: Usernames to assign to the project
         :param label_schema: Optional, label schema relative to the project.
             If provided, then label_names is ignored
             If unspecified, the default workspace is used.
+        :param label_groups: Optional. label group metadata
+        :param labelname_to_parent: Optional. label tree structure
+        :param configurable_parameters: Optional, configurable parameters to assign
+            to the task node in the Project.
         :param empty_label_name: Optional. If an empty label needs to be created,
             this parameter is used to customize its name.
         :param is_multi_label_classification: Optional. True if created project is multi-label classification
         :param hidden: Whether to keep the project as hidden after creation.
-        :param label_groups: Optional. label group metadata
-        :param labelname_to_parent: Optional. label tree structure
+        :param keypoint_structure: Keypoint structure to assign to the project, only for Keypoint Detection projects
         :return: Created project
         """
         logger.warning("Method `create_project_single_task` is deprecated.")
@@ -293,7 +297,6 @@ def create_project_single_task(  # noqa: PLR0915, PLR0913
         if isinstance(model_template, NullModelTemplate):
             raise ModelTemplateError("A NullModelTemplate was created.")
 
-        CTX_SESSION_VAR.get().workspace_id
         project_id = ProjectRepo.generate_id()
         dataset_template = ModelTemplateList().get_by_id("dataset")
         task_node_id = TaskNodeRepo.generate_id()
@@ -323,6 +326,9 @@ def create_project_single_task(  # noqa: PLR0915, PLR0913
         task_edge = TaskEdge(from_task=image_dataset_task_node, to_task=task_node)
         task_graph.add_task_edge(task_edge)
 
+        if task_node.task_properties.task_type == TaskType.KEYPOINT_DETECTION and not keypoint_structure:
+            raise ValueError("Please provide a keypoint structure for keypoint detection projects.")
+
         project = ProjectFactory.create_project_with_task_graph(
             project_id=project_id,
             name=name,
@@ -332,6 +338,7 @@ def create_project_single_task(  # noqa: PLR0915, PLR0913
             task_graph=task_graph,
             model_templates=model_templates,
             hidden=hidden,
+            keypoint_structure=keypoint_structure,
         )
 
         project_labels: list[Label]
@@ -374,7 +381,7 @@ def create_project_single_task(  # noqa: PLR0915, PLR0913
                 label_groups=label_groups, labelname_to_label=labelname_to_label
             )
 
-            # labels not have an explicite grouping should be included to an exclusive_group
+            # labels not have an explicit grouping should be included to an exclusive_group
             ungrouped_label_names = [label for label in project_labels if label.name not in grouped_label_names]
             exclusive_group = LabelGroup(
                 name="labels",
diff --git a/interactive_ai/services/api/schemas/projects/requests/put/keypoint_edge.yaml b/interactive_ai/services/api/schemas/projects/requests/put/keypoint_edge.yaml
index 124a27413..8b3452369 100644
--- a/interactive_ai/services/api/schemas/projects/requests/put/keypoint_edge.yaml
+++ b/interactive_ai/services/api/schemas/projects/requests/put/keypoint_edge.yaml
@@ -5,4 +5,6 @@ properties:
   nodes:
     type: array
     items:
-      $ref: '../../../mongo_id.yaml'
\ No newline at end of file
+      anyOf:
+        - type: string
+        - $ref: '../../../mongo_id.yaml'
\ No newline at end of file
diff --git a/interactive_ai/services/api/schemas/projects/requests/put/keypoint_position.yaml b/interactive_ai/services/api/schemas/projects/requests/put/keypoint_position.yaml
index b01f69e34..dd18a35a2 100644
--- a/interactive_ai/services/api/schemas/projects/requests/put/keypoint_position.yaml
+++ b/interactive_ai/services/api/schemas/projects/requests/put/keypoint_position.yaml
@@ -5,7 +5,9 @@ required:
   - y
 properties:
   label:
-    $ref: '../../../mongo_id.yaml'
+    anyOf:
+      - type: string
+      - $ref: '../../../mongo_id.yaml'
   x:
     type: number
     format: float
diff --git a/interactive_ai/services/dataset_ie/app/communication/helpers/import_utils.py b/interactive_ai/services/dataset_ie/app/communication/helpers/import_utils.py
index 2e5cc7d64..6a06c9d55 100644
--- a/interactive_ai/services/dataset_ie/app/communication/helpers/import_utils.py
+++ b/interactive_ai/services/dataset_ie/app/communication/helpers/import_utils.py
@@ -28,6 +28,7 @@
     Domain.ANOMALY_DETECTION,
     Domain.ANOMALY_SEGMENTATION,
     Domain.ROTATED_DETECTION,
+    Domain.KEYPOINT_DETECTION,
 ]
 
 
@@ -142,6 +143,7 @@ def get_validated_task_type(cls, project: Project) -> TaskType:
             TaskType.ANOMALY_DETECTION,
             TaskType.ANOMALY_SEGMENTATION,
             TaskType.ROTATED_DETECTION,
+            TaskType.KEYPOINT_DETECTION,
         ]
 
         trainable_tasks = project.get_trainable_task_nodes()
diff --git a/interactive_ai/services/director/app/coordination/dataset_manager/dataset_counter_config.py b/interactive_ai/services/director/app/coordination/dataset_manager/dataset_counter_config.py
index 430c1ce28..c9ac97d7d 100644
--- a/interactive_ai/services/director/app/coordination/dataset_manager/dataset_counter_config.py
+++ b/interactive_ai/services/director/app/coordination/dataset_manager/dataset_counter_config.py
@@ -127,5 +127,5 @@ class KeypointDetectionCounterConfig(DatasetCounterConfig):
         description="The minimum number of new annotations required "
         "before auto-train is triggered. Auto-training will start every time "
         "that this number of annotations is created.",
-        visible_in_ui=False,
+        visible_in_ui=True,
     )
diff --git a/interactive_ai/services/resource/app/communication/rest_data_validator/project_rest_validator.py b/interactive_ai/services/resource/app/communication/rest_data_validator/project_rest_validator.py
index c3cc05f01..65f5e376b 100644
--- a/interactive_ai/services/resource/app/communication/rest_data_validator/project_rest_validator.py
+++ b/interactive_ai/services/resource/app/communication/rest_data_validator/project_rest_validator.py
@@ -670,7 +670,7 @@ def _validate_keypoint_structure(data: dict[str, Any], labels: list[LabelPropert
         :raises NodeNameNotInLabelsException: if a node name does not match any of the label names
         :raises NodePositionIsOutOfBoundsException: if a node is out of bounds (not in the range [0.0, 1.0])
         """
-        existing_labels = [label.name for label in labels] + [label.id for label in labels]
+        existing_labels = [label.name for label in labels] + [str(label.id) for label in labels]
         pipeline_data = data[PIPELINE]
         duplicate_list = []
         is_anomaly_reduced = FeatureFlagProvider.is_enabled(FeatureFlag.FEATURE_FLAG_ANOMALY_REDUCTION)
diff --git a/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/convert_utils.py b/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/convert_utils.py
index 371c697f0..d19c05125 100644
--- a/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/convert_utils.py
+++ b/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/convert_utils.py
@@ -424,7 +424,7 @@ def get_label_annotation(  # noqa: C901
             # e.g.) 1 <- a0, 1 <- a1, 2 <- b0, 2 <- b1, [1, 2], [a0, a1], [b0, b1]
             # if an item is annotated to 'a0' and 'b0',
             # it disobeys the multi-label rule after including ancestors of 'a0' and 'b0'
-            # becaus '1' and '2' are grouped together.
+            # because '1' and '2' are grouped together.
             # In this case, we remove 'b0' and all ancestors of 'b0'
             multi_label_error = False
             for sc_label in sc_labels_for_dm_label:
@@ -649,7 +649,7 @@ def get_labels_mapper_from_dataset(
         :param dm_categories: Categories of datumaro dataset to map.
         :param dm_infos: Infos of datumaro dataset to map.
         :param sc_labels: SC labels.
-        :param domain: Lable domain. We should provide special mapping for anomaly labels.
+        :param domain: Label domain. We should provide special mapping for anomaly labels.
         :return: Method that return sc label corresponding to datumaro label id.
         """
         dm_label_mapper = ConvertUtils.get_dm_label_mapper(dm_categories, domain)
@@ -699,10 +699,14 @@ def get_labels_mapper_from_labels_map(dm_categories: dm.CategoriesInfo, labels_m
         :return: method mapping dm label id to sc label
         """
         dm_labels: dm.LabelCategories = dm_categories[dm.AnnotationType.label]
+        dm_points: dm.PointsCategories | None = dm_categories.get(dm.AnnotationType.points, None)
 
         def _get_sc_label(dm_label_id: int | str) -> Label | None:
             try:
-                dm_label_name = dm_labels[dm_label_id].name if isinstance(dm_label_id, int) else dm_label_id
+                if dm_points:
+                    dm_label_name = dm_points.items[0].labels[dm_label_id]
+                else:
+                    dm_label_name = dm_labels[dm_label_id].name if isinstance(dm_label_id, int) else dm_label_id
                 return labels_map[dm_label_name]
             except KeyError:
                 return NullLabel()
@@ -715,7 +719,7 @@ def get_sc_label_to_group_id(label_schema: LabelSchema) -> dict[Label, ID]:
         Mapping of sc_label to group id
 
         :param label_schema: label_schema of target sc project
-        :return: mapping of sc_label to all ancester labels
+        :return: mapping of sc_label to all ancestor labels
         """
         sc_label_to_group_id = {}
         for label_group in label_schema.get_groups(include_empty=False):
@@ -726,11 +730,11 @@ def get_sc_label_to_group_id(label_schema: LabelSchema) -> dict[Label, ID]:
     @staticmethod
     def get_sc_label_to_all_parents(sc_labels: list[Label], label_schema: LabelSchema) -> dict[Label, list[Label]]:
         """
-        Mapping of sc_label to all ancester labels
+        Mapping of sc_label to all ancestor labels
 
         :param sc_labels: list of sc_label
         :param label_schema: label_schema of target sc project
-        :return: mapping of sc_label to all ancester labels
+        :return: mapping of sc_label to all ancestor labels
         """
         sc_label_to_all_parents = defaultdict(list)
         for sc_label in sc_labels:
@@ -782,10 +786,10 @@ def get_label_metadata(  # noqa: C901, PLR0912
         :param selected_labels: labels selected by a user for being imported
         :param project_type: Geti project type
         :param include_all_labels: if True, ignore selected_labels then include all possible labels for each task_type
-        :return: label_groups metadata, hierachical labeling tree, list of label names
+        :return: label_groups metadata, hierarchical labeling tree, list of label names
         """
         # Collect the label names from the categories()
-        # that are utilized to construct a hierachical labeling structure or LabelGroup
+        # that are utilized to construct a hierarchical labeling structure or LabelGroup
         label_groups: list[dict[str, Any]] = []
         labelname_to_parent: dict[str, str] = {}
 
@@ -903,6 +907,9 @@ def get_keypoint_structure(
                     if not include_all_labels and not any(label in selected_labels for label in joint_names):
                         continue
                     structure["edges"].append({"nodes": list(joint_names)})
-                    # structure["positions"].append(???) TODO CVS-156570
+                for i in range(0, len(cat.positions), 2):
+                    structure["positions"].append(
+                        {"label": cat.labels[i // 2], "x": cat.positions[i], "y": cat.positions[i + 1]}
+                    )
 
         return structure
diff --git a/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/import_utils.py b/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/import_utils.py
index 597e06997..6d678f731 100644
--- a/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/import_utils.py
+++ b/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/import_utils.py
@@ -70,6 +70,7 @@ class ImportErrorDetail:
     Domain.ANOMALY_DETECTION,
     Domain.ANOMALY_SEGMENTATION,
     Domain.ROTATED_DETECTION,
+    Domain.KEYPOINT_DETECTION,
 ]
 
 
@@ -124,8 +125,8 @@ def is_dataset_from_multi_label_classification(
         """
         Check if given dm_dataset is exported from multi-label classification
 
-        :param dm_categories: Categories of Datumaro dataset obejct
-        :param dm_infos: Infos of Datumaro dataset obejct
+        :param dm_categories: Categories of Datumaro dataset object
+        :param dm_infos: Infos of Datumaro dataset object
         :return: True if dm_dataset is exported from multi-label classification project
         """
         project_type = ImportUtils.get_exported_project_type(dm_infos)
@@ -149,7 +150,7 @@ def get_exported_project_type(dm_infos: dict[str, Any]) -> GetiProjectType:
         """
         Find the Geti project type where dm_dataset is exported from
 
-        :param dm_infos: Infos of Datumaro dataset obejct
+        :param dm_infos: Infos of Datumaro dataset object
         :return: Geti project type
         """
         project_task_type: str = dm_infos.get("GetiProjectTask", "NONE")
@@ -170,8 +171,8 @@ def is_dataset_from_hierarchical_classification(
         """
         Check if given dm_dataset is exported from hierarchical classification
 
-        :param dm_categories: Categories of Datumaro dataset obejct
-        :param dm_infos: Infos of Datumaro dataset obejct
+        :param dm_categories: Categories of Datumaro dataset object
+        :param dm_infos: Infos of Datumaro dataset object
         :return: True if dm_dataset is exported from hierarchical classification project
         """
         project_type = ImportUtils.get_exported_project_type(dm_infos)
@@ -251,7 +252,7 @@ def _validate_annotations(
         :param item: dataset item
         :param label_categories: label categories within a dataset
         :param label_name_to_group: mapping between label names and label group names
-        :return: number of label, bbox, mask annotations within a item and multi-label flag
+        :return: number of label, bbox, mask annotations within an item and multi-label flag
         """
         number_of_labels: dict[str, int] = defaultdict(lambda: 0)
         multi_label_flag: bool = False
@@ -272,6 +273,8 @@ def _validate_annotations(
                 dm.AnnotationType.ellipse,
             ]:
                 number_of_labels["mask"] += 1
+            elif ann.type == dm.AnnotationType.points:
+                number_of_labels["points"] += 1
 
         return number_of_labels, multi_label_flag
 
@@ -318,6 +321,8 @@ def _validate_dataset(
                 reports["items_missing_annotation_det"].add((item.id, item.subset))
             if number_of_labels["mask"] == 0:
                 reports["items_missing_annotation_seg"].add((item.id, item.subset))
+            if number_of_labels["points"] == 0:
+                reports["items_missing_annotation_key"].add((item.id, item.subset))
 
         return reports
 
@@ -331,7 +336,7 @@ def collect_validation_warnings(
     ) -> ImportErrorDetail:
         """
         Collect number of non-actionable errors (warnings) in dataset using different validators
-        for supported task types in dataset, skip classification since classificaiton errors
+        for supported task types in dataset, skip classification since classification errors
         were collected earlier
 
         :param dm_dataset: datumaro dataset to validate for warnings
@@ -435,8 +440,7 @@ def get_label_to_ann_types(
         :return: dictionary mapping label names to a set of dm annotation type
         """
         label_cat: dm.LabelCategories = dm_dataset.categories()[dm.AnnotationType.label]
-
-        # label_names = [label_item.name for label_item in label_cat]
+        label_points: dm.PointsCategories | None = dm_dataset.categories().get(dm.AnnotationType.points, None)
 
         label_idx_to_ann_types = defaultdict(set)
         total = len(dm_dataset)
@@ -447,7 +451,10 @@ def get_label_to_ann_types(
                 continue
             for dm_ann in dm_item.annotations:
                 label_id = getattr(dm_ann, "label", None)
-                if label_id is not None:
+                if label_points:
+                    # for keypoint annotations, we force the label_id to be 0 which is the first label in the dm dataset
+                    label_idx_to_ann_types[0].add(dm_ann.type)
+                elif label_id:
                     label_idx_to_ann_types[label_id].add(dm_ann.type)
                 # TODO: need to check if this is needed.
                 # for dm_attr_key in dm_ann.attributes:
@@ -472,7 +479,7 @@ def get_valid_project_labels(  # noqa: C901
 
         :param project_type: Geti project type
         :param dm_infos: infos of datumaro dataset
-        :param dm_categories: Categories of Datumaro dataset obejct
+        :param dm_categories: Categories of Datumaro dataset object
         :param label_to_ann_types: A mapping of label names in dataset to ann_types with which they appear
         :param selected_labels: label_names that a user selected to include in the created project
         :param include_all_labels: If True, ignore selected_labels then include all possible labels for each task_type
@@ -776,7 +783,7 @@ def get_project_type(project: Project) -> GetiProjectType:
     @staticmethod
     def project_type_to_label_domain(project_type: GetiProjectType) -> Domain:
         """
-        Get an label domain of interest by project_type
+        Get a label domain of interest by project_type
 
         :param project_type: project_type
         :return: label domain related to the project_type
@@ -792,7 +799,7 @@ def project_type_to_label_domain(project_type: GetiProjectType) -> Domain:
             GetiProjectType.ANOMALY_SEGMENTATION: Domain.ANOMALY_SEGMENTATION,
             GetiProjectType.INSTANCE_SEGMENTATION: Domain.INSTANCE_SEGMENTATION,
             GetiProjectType.ROTATED_DETECTION: Domain.ROTATED_DETECTION,
-            # For CHAINED_DETECTION_CLSSIFICATION project, we interest in bbox annotations in dm_dataset
+            # For CHAINED_DETECTION_CLASSIFICATION project, we interest in bbox annotations in dm_dataset
             GetiProjectType.CHAINED_DETECTION_CLASSIFICATION: Domain.DETECTION,
             # For CHAINED_DETECTION_SEGMENTATION project, we interest in bbox, polygon, and ellipse annotations
             # Note that Domain.SEGMENTATION includes all of them.
@@ -839,6 +846,7 @@ def get_validated_task_type(cls, project: Project) -> TaskType:
             TaskType.ANOMALY_DETECTION,
             TaskType.ANOMALY_SEGMENTATION,
             TaskType.ROTATED_DETECTION,
+            TaskType.KEYPOINT_DETECTION,
         ]
 
         trainable_tasks = project.get_trainable_task_nodes()
diff --git a/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/mappers/annotation_scene_mapper.py b/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/mappers/annotation_scene_mapper.py
index bb796b1ae..a1addaa41 100644
--- a/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/mappers/annotation_scene_mapper.py
+++ b/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/mappers/annotation_scene_mapper.py
@@ -1,6 +1,6 @@
 # Copyright (C) 2022-2025 Intel Corporation
 # LIMITED EDGE SOFTWARE DISTRIBUTION LICENSE
-"""This module implements annotation scene mapper for conversion between SC AnnotationScene and Datumaro annotations"""
+"""This module implements a mapper for conversion between Geti AnnotationScene and Datumaro annotations"""
 
 from itertools import chain
 
@@ -13,7 +13,7 @@
 
 
 class LabelMap:
-    """Map Datumaro label index (integer) to SC Label"""
+    """Map Datumaro label index (integer) to Geti Label"""
 
     def __init__(
         self,
@@ -35,7 +35,7 @@ def __getitem__(self, key: int) -> Label:
         return self.label_map[key]
 
     def get_dm_label_by_sc_label_id(self, label_id: ID) -> int | None:
-        """Get Datumaro label id (int) from the SC label id (ID). If cannot find, return None."""
+        """Get Datumaro label id (int) from the Geti label id (ID). If cannot find, return None."""
         dm_label, _ = self.label_categories.find(str(label_id))
         return dm_label
 
@@ -64,13 +64,8 @@ def forward(self, instance: AnnotationScene) -> list[dm.Annotation]:
         for sc_ann in instance.annotations:
             if not isinstance(sc_ann.shape, Keypoint):
                 # For task-chain, annotations that only contain labels from other tasks will return None and are removed
-                if (
-                    dm_ann := self._forward_ann(
-                        annotation=sc_ann,
-                        width=instance.media_width,
-                        height=instance.media_height,
-                    )
-                ) is not None:
+                dm_ann = self._forward_ann(annotation=sc_ann, width=instance.media_width, height=instance.media_height)
+                if dm_ann:
                     dm_anns.append(dm_ann)
             else:
                 sc_keypoint_anns.append(sc_ann)
diff --git a/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/mappers/label_mapper.py b/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/mappers/label_mapper.py
index a670a95e3..5236f316b 100644
--- a/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/mappers/label_mapper.py
+++ b/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/mappers/label_mapper.py
@@ -8,6 +8,7 @@
 from datumaro.components.annotation import GroupType as DmGroupType
 from geti_types import ID
 from iai_core.entities.color import Color
+from iai_core.entities.keypoint_structure import KeypointStructure
 from iai_core.entities.label import Label
 from iai_core.entities.label_schema import LabelGroupType, LabelSchema
 
@@ -59,8 +60,8 @@ class LabelTreeMapper:
     color_key = "__color__"
 
     @classmethod
-    def forward(
-        cls, label_schema: LabelSchema, include_empty: bool = False
+    def forward(  # noqa: C901
+        cls, label_schema: LabelSchema, include_empty: bool = False, keypoint_structure: KeypointStructure | None = None
     ) -> tuple[dm.LabelCategories, dm.PointsCategories]:
         """Convert SC label list and their tree info to Datumaro LabelCategories"""
         # labels = label_schema.get_labels(include_empty=include_empty)
@@ -78,7 +79,17 @@ def forward(
 
         label_cat = dm.LabelCategories()
         point_cat = dm.PointsCategories()
-        point_cat.add(label_id=0, labels=[str(label.id_) for label in labels], joints=[])
+        if keypoint_structure:
+            label_id_to_idx = {label.id_: idx for idx, label in enumerate(labels)}
+            joints = []
+            for edge in keypoint_structure._edges:
+                node_1 = label_id_to_idx[edge.node_1]
+                node_2 = label_id_to_idx[edge.node_2]
+                joints.append([node_1, node_2])
+            positions = []
+            for position in keypoint_structure._positions:
+                positions.extend([position.x, position.y])
+            point_cat.add(label_id=0, labels=[str(label.id_) for label in labels], joints=joints, positions=positions)
 
         for label in labels:
             parent = parent_map.get(label)
@@ -125,11 +136,13 @@ class LabelSchemaMapper:
     """Mapping LabelSchema between Datumaro and SC"""
 
     @staticmethod
-    def forward(label_schema: LabelSchema, include_empty: bool = False) -> DmLabelSchemaInfo:
+    def forward(
+        label_schema: LabelSchema, include_empty: bool = False, keypoint_structure: KeypointStructure | None = None
+    ) -> DmLabelSchemaInfo:
         """Convert SC LabelSchema to DmLabelSchemaInfo"""
 
         label_schema_id = label_schema.id_
-        label_cat, point_cat = LabelTreeMapper.forward(label_schema, include_empty)
+        label_cat, point_cat = LabelTreeMapper.forward(label_schema, include_empty, keypoint_structure)
         label_cat = LabelGroupsMapper.update(label_cat, label_schema, include_empty)
 
         mask_cat = dm.MaskCategories(
diff --git a/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/sc_extractor.py b/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/sc_extractor.py
index d114efd1c..163ba0f51 100644
--- a/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/sc_extractor.py
+++ b/interactive_ai/workflows/geti_domain/common/jobs_common_extras/datumaro_conversion/sc_extractor.py
@@ -1,6 +1,6 @@
 # Copyright (C) 2022-2025 Intel Corporation
 # LIMITED EDGE SOFTWARE DISTRIBUTION LICENSE
-"""This module implements conversion from SC Dataset to Datumaro dataset."""
+"""This module implements conversion from Geti Dataset to Datumaro dataset."""
 
 import logging
 import os
@@ -25,6 +25,7 @@
 from datumaro import LabelCategories as dm_LabelCategories
 from datumaro import MaskCategories as dm_MaskCategories
 from datumaro import Points as dm_Points
+from datumaro import PointsCategories as dm_PointCategories
 from datumaro import Polygon as dm_Polygon
 from datumaro import Video as dm_Video
 from datumaro import VideoFrame as dm_VideoFrame
@@ -43,12 +44,21 @@
 from iai_core.entities.dataset_storage import DatasetStorage
 from iai_core.entities.datasets import Dataset, NullDataset
 from iai_core.entities.image import Image
+from iai_core.entities.keypoint_structure import KeypointStructure
 from iai_core.entities.label import Domain
 from iai_core.entities.label_schema import LabelGroupType, LabelSchema
 from iai_core.entities.shapes import Ellipse, Keypoint, Polygon, Rectangle
 from iai_core.entities.subset import Subset
 from iai_core.entities.video import Video, VideoFrame
-from iai_core.repos import AnnotationSceneRepo, DatasetRepo, ImageRepo, LabelRepo, VideoAnnotationRangeRepo, VideoRepo
+from iai_core.repos import (
+    AnnotationSceneRepo,
+    DatasetRepo,
+    ImageRepo,
+    LabelRepo,
+    ProjectRepo,
+    VideoAnnotationRangeRepo,
+    VideoRepo,
+)
 
 from jobs_common_extras.datumaro_conversion.mappers.annotation_scene_mapper import AnnotationSceneMapper, LabelMap
 from jobs_common_extras.datumaro_conversion.mappers.dataset_item_mapper import DatasetItemMapper
@@ -69,7 +79,7 @@
 
 class ScExtractor(dm_DatasetBase):
     """
-    Represents the SC dataset as a lazy dataset for Datumaro.
+    Represents the Geti dataset as a lazy dataset for Datumaro.
     """
 
     VERSION = "1.0"
@@ -96,6 +106,7 @@ def __init__(
             workspace_id=dataset_storage_identifier.workspace_id,
             project_id=dataset_storage_identifier.project_id,
         )
+        project = ProjectRepo().get_by_id(dataset_storage_identifier.project_id)
         label_repo = LabelRepo(project_identifier=project_identifier)
         self._label_id_to_label = {label.id_: label for label in label_repo.get_all()}
 
@@ -109,7 +120,9 @@ def __init__(
         self._init_infos()
 
         self._categories: dm_CategoriesInfo = {}
-        self._init_categories(sc_dataset=self._dataset, label_schema=label_schema)
+        self._init_categories(
+            sc_dataset=self._dataset, label_schema=label_schema, keypoint_structure=project.keypoint_structure
+        )
         self._use_subset = use_subset
         self._set_name_mapper()
 
@@ -125,16 +138,22 @@ def _init_infos(self) -> None:
         """
         self._infos = {"ScExtractorVersion": ScExtractor.VERSION}
 
-    def _init_categories(self, sc_dataset: Dataset, label_schema: LabelSchema) -> None:  # noqa: ARG002
+    def _init_categories(
+        self,
+        sc_dataset: Dataset,  # noqa: ARG002
+        label_schema: LabelSchema,
+        keypoint_structure: KeypointStructure | None,
+    ) -> None:
         label_cat = dm_LabelCategories()
         mask_cat = dm_MaskCategories()
-        sc_labels = label_schema.get_labels(include_empty=False)
+        point_cat = dm_PointCategories()
+        geti_labels = label_schema.get_labels(include_empty=False)
 
         # Collect label names that are necessary to be exported
         valid_labelnames: set[str] = set()
-        valid_labelnames.update([sc_label.name for sc_label in sc_labels])
+        valid_labelnames.update([sc_label.name for sc_label in geti_labels])
 
-        for i, sc_label in enumerate(sc_labels):
+        for i, sc_label in enumerate(geti_labels):
             if label_schema is not None:
                 sc_parent = label_schema.label_tree.get_parent(sc_label)
                 if sc_parent is not None:
@@ -147,8 +166,19 @@ def _init_categories(self, sc_dataset: Dataset, label_schema: LabelSchema) -> No
                 label_cat.add(sc_label.name)
             mask_cat.colormap[i] = sc_label.color.rgb_tuple
 
+        if keypoint_structure:
+            joints = []
+            for edge in keypoint_structure._edges:
+                node_1 = self._label_id_to_idx[edge.node_1] + 1
+                node_2 = self._label_id_to_idx[edge.node_2] + 1
+                joints.append([node_1, node_2])  # Joints start at 1 index
+            positions = []
+            for position in keypoint_structure._positions:
+                positions.extend([position.x, position.y])
+            point_cat.add(label_id=0, labels=[label.name for label in geti_labels], joints=joints, positions=positions)
+
         # Old version of datumaro doesn't have 'add_label_group' function
-        # We thus check the existance of function before the function call
+        # We thus check the existence of function before the function call
         if label_schema is not None:
             label_groups = label_schema.get_groups()
             for label_group in label_groups:
@@ -171,6 +201,7 @@ def _init_categories(self, sc_dataset: Dataset, label_schema: LabelSchema) -> No
         self._categories = {
             dm_AnnotationType.label: label_cat,
             dm_AnnotationType.mask: mask_cat,
+            dm_AnnotationType.points: point_cat,
         }
 
         self._label_name_to_all_parent = self.get_label_to_all_parents()
@@ -251,7 +282,7 @@ def _convert_annotations(self, annotations: list[Annotation], width: int, height
                     )
                 )
             elif isinstance(shape, Rectangle):
-                # Classification is represented as full boxes in SC
+                # Classification is represented as full boxes in Geti
                 if Rectangle.is_full_box(shape):
                     # hierarchical classification task may store multiple-labels
                     # e.g.) in "rectangle" -> "square" structure,
@@ -300,15 +331,15 @@ def _convert_annotations(self, annotations: list[Annotation], width: int, height
             else:
                 raise NotImplementedError(f"Unsupported conversion to DM of {sc_ann.__class__.__name__} items")
 
-            if keypoints and visibilities:
-                dm_anns.append(
-                    dm_Points(
-                        points=keypoints,
-                        visibility=visibilities,
-                        label=primary_label_id,
-                        attributes=keypoint_labels,
-                    )
+        if keypoints and visibilities:
+            dm_anns.append(
+                dm_Points(
+                    points=keypoints,
+                    visibility=visibilities,
+                    label=0,
+                    attributes=keypoint_labels,
                 )
+            )
 
         return dm_anns
 
@@ -318,9 +349,9 @@ def _convert_item(
         video_root: str | None = None,
     ) -> dm_DatasetItem:
         """
-        Convert SC dataset item to DM dataset item.
+        Convert Geti dataset item to DM dataset item.
 
-        :param sc_item: SC dataset item
+        :param sc_item: Geti dataset item
         :param video_root: If this value is None, save the video as individual frame images.
                            Otherwise, save the video in its original format.
         :return: Datumaro dataset item
@@ -396,7 +427,7 @@ class DatasetItemWithFuture:
 
 class ScExtractorForFlyteJob(ScExtractor):
     """
-    Represents the SC dataset as a lazy dataset for Datumaro.
+    Represents the Geti dataset as a lazy dataset for Datumaro.
     It is used for Flyte job.
     """
 
@@ -418,16 +449,20 @@ def __init__(
     def _set_name_mapper(self):
         self._name_mapper = IDMapper
 
-    def _init_categories(self, sc_dataset: Dataset, label_schema: LabelSchema | None) -> None:
+    def _init_categories(
+        self, sc_dataset: Dataset, label_schema: LabelSchema | None, keypoint_structure: KeypointStructure | None = None
+    ) -> None:
         if label_schema is None:
             raise RuntimeError("label_schema=None is not allowed.")
 
-        dm_label_schema_info = LabelSchemaMapper.forward(label_schema=label_schema, include_empty=True)
+        dm_label_schema_info = LabelSchemaMapper.forward(
+            label_schema=label_schema, include_empty=True, keypoint_structure=keypoint_structure
+        )
 
         self._categories = {
-            dm_AnnotationType.label: dm_label_schema_info.label_cat,
-            dm_AnnotationType.mask: dm_label_schema_info.mask_cat,
-            dm_AnnotationType.points: dm_label_schema_info.point_cat,
+            dm_AnnotationType.label: dm_label_schema_info.label_cat,  # label names: name, parent, attributes
+            dm_AnnotationType.mask: dm_label_schema_info.mask_cat,  # label colour: rgb
+            dm_AnnotationType.points: dm_label_schema_info.point_cat,  # keypoint label: position, visibility
         }
 
         self.dataset_item_mapper = DatasetItemMapper(
@@ -521,7 +556,7 @@ class ProgressConfig(NamedTuple):
 
 class ScExtractorFromDatasetStorage(ScExtractor):
     """
-    Represents the SC dataset storage as a lazy dataset for Datumaro.
+    Represents the Geti dataset storage as a lazy dataset for Datumaro.
     """
 
     def __init__(
@@ -534,10 +569,10 @@ def __init__(
         progress_config: ProgressConfig | None = None,
     ) -> None:
         """
-        Represents the SC dataset storage as a lazy dataset for Datumaro.
+        Represents the Geti dataset storage as a lazy dataset for Datumaro.
 
-        :param dataset_storage: SC dataset storage
-        :param label_schema: SC label schema
+        :param dataset_storage: Geti dataset storage
+        :param label_schema: Geti label schema
         :param use_subset: Whether to set subset name from sc item or not
         :param include_unannotated: Whether to include unannotated media or not
         :param video_export_config: If this is given, save video as its original format.
@@ -599,7 +634,7 @@ def __iter__(self) -> Iterator[dm_DatasetItem]:
         for i, identifier in enumerate(self._identifiers):
             if self._progress_config:
                 # Datumaro's export iterates the dataset several times while exporting.
-                # This is trickey, but we need to consider the implementation detail of datumaro here.
+                # This is tricky, but we need to consider the implementation detail of datumaro here.
                 if i == 0:
                     self._iter_count += 1
                     logger.info(
diff --git a/interactive_ai/workflows/geti_domain/common/pyproject.toml b/interactive_ai/workflows/geti_domain/common/pyproject.toml
index a971826ed..6f47ec2e4 100644
--- a/interactive_ai/workflows/geti_domain/common/pyproject.toml
+++ b/interactive_ai/workflows/geti_domain/common/pyproject.toml
@@ -27,12 +27,12 @@ evaluation = [
 ]
 
 shard-dataset = [
-    "datumaro==1.8.0",
+    "datumaro==1.10.0",
 ]
 
 datumaro-conversion = [
     "media-utils",
-    "datumaro==1.8.0",
+    "datumaro==1.10.0",
 ]
 
 
diff --git a/interactive_ai/workflows/geti_domain/common/tests/fixtures/dataset.py b/interactive_ai/workflows/geti_domain/common/tests/fixtures/dataset.py
index 968d8740f..5aea67c45 100644
--- a/interactive_ai/workflows/geti_domain/common/tests/fixtures/dataset.py
+++ b/interactive_ai/workflows/geti_domain/common/tests/fixtures/dataset.py
@@ -11,6 +11,7 @@
 from iai_core.entities.dataset_item import DatasetItem
 from iai_core.entities.datasets import Dataset
 from iai_core.entities.image import Image
+from iai_core.entities.keypoint_structure import KeypointEdge, KeypointPosition, KeypointStructure
 from iai_core.entities.label_schema import LabelSchema
 from iai_core.entities.subset import Subset
 from iai_core.entities.video import VideoFrame
@@ -203,6 +204,15 @@ def fxt_dataset_and_label_schema(
     request: pytest.FixtureRequest,
 ) -> tuple[DatasetStorageIdentifier, Dataset, LabelSchema]:
     model_template_id = request.param
+    keypoint_structure = None
+    if model_template_id == "keypoint_detection":
+        keypoint_structure = KeypointStructure(
+            edges=[KeypointEdge(node_1=ID("node_1"), node_2=ID("node_2"))],
+            positions=[
+                KeypointPosition(node=ID("node_1"), x=0.123, y=0.123),
+                KeypointPosition(node=ID("node_2"), x=1, y=1),
+            ],
+        )
     project, label_schema = generate_random_annotated_project(
         request,
         name="__Test dataset entities (1)",
@@ -211,13 +221,14 @@ def fxt_dataset_and_label_schema(
         number_of_images=12,
         number_of_videos=1,
         # This is required by OTX training classification task code
-        # We need to compare `Label` equivalance
+        # We need to compare `Label` equivalence
         # `color (rgba)` and `hotkey` are used to the comparison.
         label_configs=[
             {"name": "rectangle", "color": "#00ff00ee", "hotkey": "ctrl-1"},
             {"name": "ellipse", "color": "#0000ff99", "hotkey": "ctrl-2"},
             {"name": "triangle", "color": "#ff000011", "hotkey": "ctrl-3"},
         ],
+        keypoint_structure=keypoint_structure,
     )
 
     (
diff --git a/interactive_ai/workflows/geti_domain/common/tests/test_helpers.py b/interactive_ai/workflows/geti_domain/common/tests/test_helpers.py
index a7f233d01..50796463b 100644
--- a/interactive_ai/workflows/geti_domain/common/tests/test_helpers.py
+++ b/interactive_ai/workflows/geti_domain/common/tests/test_helpers.py
@@ -273,6 +273,7 @@ def generate_random_annotated_project(
     max_size_shape: int = 100,
     configurable_parameters: HyperParameters[ConfigurableParameters] | None = None,
     label_configs=None,
+    keypoint_structure=None,
 ) -> tuple[Project, LabelSchema]:
     """
     Will create a randomly annotated project in the default workspace with images
@@ -295,6 +296,7 @@ def generate_random_annotated_project(
     :param configurable_parameters: [Optionally] Set the configurable parameters for
         the newly created task in the project
     :param label_configs: List of label configuration which is a dictionary of label attributes
+    :param keypoint_structure: Keypoint structure to assign to the project, only for Keypoint Detection projects
     :return: Generated project
     """
 
@@ -324,6 +326,7 @@ def generate_random_annotated_project(
         labels=label_configs,
         model_template_id=model_template_id,
         configurable_parameters=parameter_data,
+        keypoint_structure=keypoint_structure,
     )
     dataset_storage = project_input.get_training_dataset_storage()
     dataset_storage_identifier = dataset_storage.identifier
diff --git a/interactive_ai/workflows/geti_domain/common/tests/unit/extras/datumaro_conversion/test_mapper.py b/interactive_ai/workflows/geti_domain/common/tests/unit/extras/datumaro_conversion/test_mapper.py
index b24faa4fc..07ea1bb76 100644
--- a/interactive_ai/workflows/geti_domain/common/tests/unit/extras/datumaro_conversion/test_mapper.py
+++ b/interactive_ai/workflows/geti_domain/common/tests/unit/extras/datumaro_conversion/test_mapper.py
@@ -13,11 +13,12 @@
 from iai_core.entities.label import Label
 from iai_core.entities.label_schema import LabelSchema
 from iai_core.entities.scored_label import ScoredLabel
-from iai_core.entities.shapes import Ellipse, Point, Polygon, Rectangle
+from iai_core.entities.shapes import Ellipse, Keypoint, Point, Polygon, Rectangle
 
 from jobs_common_extras.datumaro_conversion.mappers.annotation_scene_mapper import AnnotationSceneMapper, LabelMap
 from jobs_common_extras.datumaro_conversion.mappers.dataset_item_mapper import (
     EllipseMapper,
+    KeypointMapper,
     LabelMapper,
     PolygonMapper,
     RectangleMapper,
@@ -120,6 +121,22 @@ def test_forward(self) -> None:
         assert mapped_polygon == expected_mapped_polygon
 
 
+class TestKeypointMapper:
+    def test_forward(self) -> None:
+        modification_date = datetime.datetime.now(tz=datetime.timezone.utc)
+        keypoint = Keypoint(x=0.5, y=0.6, is_visible=True, modification_date=modification_date)
+        expected_mapped_keypoint = {
+            "type": "KEYPOINT",
+            "points": [0.5, 0.6],
+            "modification_date": modification_date.strftime("%Y-%m-%dT%H:%M:%S.%f"),
+            "visibility": [dm.Points.Visibility.visible],
+        }
+
+        mapped_keypoint = KeypointMapper.forward(keypoint)
+
+        assert mapped_keypoint == expected_mapped_keypoint
+
+
 class TestShapeMapper:
     @pytest.mark.parametrize(
         "shape",
diff --git a/interactive_ai/workflows/geti_domain/common/uv.lock b/interactive_ai/workflows/geti_domain/common/uv.lock
index b7520e7d8..d1ab6ae3f 100644
--- a/interactive_ai/workflows/geti_domain/common/uv.lock
+++ b/interactive_ai/workflows/geti_domain/common/uv.lock
@@ -551,7 +551,7 @@ wheels = [
 
 [[package]]
 name = "datumaro"
-version = "1.8.0"
+version = "1.10.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "attrs" },
@@ -572,6 +572,7 @@ dependencies = [
     { name = "ovmsclient" },
     { name = "pandas" },
     { name = "pillow" },
+    { name = "portalocker" },
     { name = "protobuf" },
     { name = "pyarrow" },
     { name = "pycocotools" },
@@ -589,11 +590,11 @@ dependencies = [
     { name = "tritonclient", extra = ["all"] },
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/12/7c/0d29f21a68e9e1543f87cb78213e5870f499cf28bee850fa519ba491e31a/datumaro-1.8.0.tar.gz", hash = "sha256:2a8ef4bd36f968ded6b6f4f56fe974431cd7bd4d1e3d9f75e447b1c928fa1dbc", size = 564692 }
+sdist = { url = "https://files.pythonhosted.org/packages/50/62/a915845b2d650ec2e2dc9f07716872228f898ff4ee7c45a729304295b3b7/datumaro-1.10.0.tar.gz", hash = "sha256:408a07fb4c74a2d832d4493c9c8001283cc0f40b02fdddc26b9e05ffb6ee8477", size = 567726 }
 wheels = [
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+    { url = "https://files.pythonhosted.org/packages/46/62/3bb463635ebac05b2603416e7c79e56ac6af7c401056246ab448dc09c8f8/datumaro-1.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1e7cee5d990cf85c246e33b8dfe21a67298fbb2a8886aa5607d97924087a0b97", size = 1167120 },
+    { url = "https://files.pythonhosted.org/packages/fc/a1/3aa0975be54a51480f83a6f7315e2d6dc31b1b446847faa4cc34589db2f8/datumaro-1.10.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:d2f41647ed54bb09ca306614203ae90f69e65e89e18d7c36ed0f75c69278ee6a", size = 1682767 },
+    { url = "https://files.pythonhosted.org/packages/84/46/035835142298a8eacea7bdc19a7b0949a7d5d33a480814666741c39a63ba/datumaro-1.10.0-cp310-cp310-win_amd64.whl", hash = "sha256:2823e930c1e4ca2c75046354d6214401498eff5f3c27c63d7a62d84958be56d5", size = 981121 },
 ]
 
 [[package]]
@@ -2237,19 +2238,20 @@ wheels = [
 
 [[package]]
 name = "orjson"
-version = "3.10.5"
+version = "3.10.7"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/f9/ba/a506ace6d9e4cb96cb4bed678fddc2605b8befe7fbbbecc309af1364b7c4/orjson-3.10.5.tar.gz", hash = "sha256:7a5baef8a4284405d96c90c7c62b755e9ef1ada84c2406c24a9ebec86b89f46d", size = 5249974 }
+sdist = { url = "https://files.pythonhosted.org/packages/9e/03/821c8197d0515e46ea19439f5c5d5fd9a9889f76800613cfac947b5d7845/orjson-3.10.7.tar.gz", hash = "sha256:75ef0640403f945f3a1f9f6400686560dbfb0fb5b16589ad62cd477043c4eee3", size = 5056450 }
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+    { url = "https://files.pythonhosted.org/packages/7f/7e/ef8522dbba112af6cc52227dcc746dd3447c7d53ea8cea35740239b547ee/orjson-3.10.7-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de817e2f5fc75a9e7dd350c4b0f54617b280e26d1631811a43e7e968fa71e3e9", size = 163955 },
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+    { url = "https://files.pythonhosted.org/packages/a6/d8/eee30caba21a8d6a9df06d2519bb0ecd0adbcd57f2e79d360de5570031cf/orjson-3.10.7-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:fdf5197a21dd660cf19dfd2a3ce79574588f8f5e2dbf21bda9ee2d2b46924d84", size = 167804 },
+    { url = "https://files.pythonhosted.org/packages/44/fe/d1d89d3f15e343511417195f6ccd2bdeb7ebc5a48a882a79ab3bbcdf5fc7/orjson-3.10.7-cp310-none-win32.whl", hash = "sha256:d374d36726746c81a49f3ff8daa2898dccab6596864ebe43d50733275c629175", size = 143010 },
+    { url = "https://files.pythonhosted.org/packages/88/8c/0e7b8d5a523927774758ac4ce2de4d8ca5dda569955ba3aeb5e208344eda/orjson-3.10.7-cp310-none-win_amd64.whl", hash = "sha256:cb61938aec8b0ffb6eef484d480188a1777e67b05d58e41b435c74b9d84e0b9c", size = 137306 },
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 [[package]]
@@ -2338,6 +2340,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/88/5f/e351af9a41f866ac3f1fac4ca0613908d9a41741cfcf2228f4ad853b697d/pluggy-1.5.0-py3-none-any.whl", hash = "sha256:44e1ad92c8ca002de6377e165f3e0f1be63266ab4d554740532335b9d75ea669", size = 20556 },
 ]
 
+[[package]]
+name = "portalocker"
+version = "3.1.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pywin32", marker = "sys_platform == 'win32'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ac/91/8bfe23e1f7f630f2061ef38b5225d9fda9068d6a30fcbc187951e678e630/portalocker-3.1.1.tar.gz", hash = "sha256:ec20f6dda2ad9ce89fa399a5f31f4f1495f515958f0cb7ca6543cef7bb5a749e", size = 43708 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/f7/60/1974cfdd5bb770568ddc6f89f3e0df4cfdd1acffd5a609dff5e95f48c6e2/portalocker-3.1.1-py3-none-any.whl", hash = "sha256:80e984e24de292ff258a5bea0e4f3f778fff84c0ae1275dbaebc4658de4aacb3", size = 19661 },
+]
+
 [[package]]
 name = "pre-commit"
 version = "4.2.0"
@@ -3350,8 +3364,8 @@ dev = [
 [package.metadata]
 requires-dist = [
     { name = "dataclasses-json", specifier = "==0.5.7" },
-    { name = "datumaro", marker = "extra == 'datumaro-conversion'", specifier = "==1.8.0" },
-    { name = "datumaro", marker = "extra == 'shard-dataset'", specifier = "==1.8.0" },
+    { name = "datumaro", marker = "extra == 'datumaro-conversion'", specifier = "==1.10.0" },
+    { name = "datumaro", marker = "extra == 'shard-dataset'", specifier = "==1.10.0" },
     { name = "flytekit", specifier = "==1.10.2" },
     { name = "flytekitplugins-pod", specifier = "==1.2.4" },
     { name = "geti-k8s-tools", editable = "../../../../libs/k8s_tools" },
diff --git a/interactive_ai/workflows/geti_domain/dataset_ie/job/utils/datumaro_parser.py b/interactive_ai/workflows/geti_domain/dataset_ie/job/utils/datumaro_parser.py
index cfc837402..cf86e6838 100644
--- a/interactive_ai/workflows/geti_domain/dataset_ie/job/utils/datumaro_parser.py
+++ b/interactive_ai/workflows/geti_domain/dataset_ie/job/utils/datumaro_parser.py
@@ -24,11 +24,12 @@
 class DatumaroProjectParser(ProjectParser):
     """
     An implementation of ProjectParser for Datumaro.
-    ProjectFactory will call the fucntions in the parser to create a project.
+    ProjectFactory will call the functions in the parser to create a project.
 
-    :param dm_dataset: Datumaro dataset instance
     :param project_name: A name of project to be created
     :param project_type: Geti project type
+    :param dm_infos: Infos of datumaro dataset
+    :param dm_categories: Categories belonging to the datumaro dataset
     :param label_to_ann_types: A mapping of label names in dataset to ann_types with which they appear
     :param selected_labels: label_names that a user selected to include in the created project
     :param color_by_label: Optional, mapping between label names and their color.
@@ -53,7 +54,6 @@ def __init__(  # noqa: PLR0913
         self._project_name: str = project_name
         self._project_type: GetiProjectType = project_type
         self._color_by_label = color_by_label if color_by_label else {}
-
         (
             self._task_names_ordered,
             self._task_name_to_task_type,
@@ -99,9 +99,9 @@ def _validate(self):
         Raise an exception if parsed data is not proper to create a project
         """
 
-        # 'Minimum 2 top-label calssifcation labels' rule
+        # 'Minimum 2 top-label classification labels' rule
         # For a classification task, at least 2 labels should be provided.
-        # Otherwise the task is ill-defined (a classification model that predicts only 1 class makes no sense).
+        # Otherwise, the task is ill-defined (a classification model that predicts only 1 class makes no sense).
         # Top-level means at the root level of the hierarchy.
         for task_name in self.get_tasks_names():
             task_type = self.get_task_type_by_name(task_name=task_name)
@@ -153,7 +153,6 @@ def _get_label_name_to_label_meta(  # noqa: C901
         :param label_groups: metadata for label group information each entry has 'name' and 'labels'
         :param label_name_to_parent: mapping from label_name to parent_name
         :param label_infos: metadata for label 'color' and 'hotkey'
-
         :return: mapping from label_name to label_meta
         """
         # Store label group name with label_name as key
@@ -165,7 +164,7 @@ def _get_label_name_to_label_meta(  # noqa: C901
                 for label_name in label_names:
                     label_name_to_group[label_name] = group_name
 
-        # label_infos optionaly has 'color, 'hotkey' meta-data
+        # label_infos optionally has 'color, 'hotkey' meta-data
         label_meta: dict[str, dict[str, Any]] = {}
         for label_info in label_infos:
             label_name = label_info["name"]
@@ -195,14 +194,14 @@ def _extract_labels_metadata_from_dm_dataset(
         include_all_labels: bool = False,
     ) -> dict[str, dict[str, dict[str, Any]]]:
         """
-        Parse Datumaro dataset instance to extracte label meta data.
-        Label meta data includes 'parent', 'group', 'color', and 'hotkey' of labels
+        Parse Datumaro dataset instance to extract label metadata.
+        Label metadata includes 'parent', 'group', 'color', and 'hotkey' of labels
 
         :param dm_infos: Infos of datumaro dataset.
         :param dm_categories: Categories of datumaro dataset.
         :param selected_labels: label_names that a user selected to include in the created project
         :param include_all_labels: if True, ignore selected_labels then include all possible labels for each task_type
-        :return: A dictionary stores label_meta with label_name as key
+        :return: A dictionary storing label_meta with label_name as key
         """
         (
             label_groups,
@@ -298,7 +297,7 @@ def _process_task_types(
         """
         Assign task_name to task_type
 
-        :param trainable_task_types: task node types that are trainable
+        :param project_type: the Geti project type
         :return: A list of task_names (used in rest api), A dictionary mapping task_name to task_type
         """
         trainable_task_types = ImportUtils.get_trainable_tasks_of_project_type(project_type=project_type)
@@ -402,7 +401,7 @@ def get_keypoint_structure(self) -> dict[str, list]:
     def _get_label_meta(self, task_name: str, label_name: str) -> dict[str, Any]:
         """
         Get the label_meta of label:label_name in the task:task_name
-        label_meta optionaly contains 'group', 'parent', 'color', and 'hotkey'
+        label_meta optionally contains 'group', 'parent', 'color', and 'hotkey'
 
         :param task_name: Name of the task node
         :param label_name: Name of the label
@@ -479,7 +478,6 @@ def parse_project_pipeline(self) -> dict[str, Any]:
         Build the 'pipeline' field of the REST API 'datasets:prepare-for-import' endpoint
         retrieving the necessary information from a DatumaroProjectParser.
 
-        :param project_parser: A parser to extract project meta-data from the dataset
         :return: dictionary with the following structure.
             e.g.)
             {
@@ -557,17 +555,6 @@ def parse_project_pipeline(self) -> dict[str, Any]:
                 FeatureFlagProvider.is_enabled(FeatureFlag.FEATURE_FLAG_KEYPOINT_DETECTION)
                 and task_type == TaskType.KEYPOINT_DETECTION
             ):
-                # need 'keypoint_structure' field in the task
-                # "keypoint_structure": [
-                #     "edges": [
-                #         {"nodes": [label1, label2]},
-                #          ...,
-                #     ],
-                #     "positions": [
-                #         {"label": label1, "x": 0.5, "y": 0.5},
-                #         ...,
-                #     ]
-                # ]
                 task["keypoint_structure"] = self.get_keypoint_structure()
 
             tasks.append(task)
@@ -595,14 +582,19 @@ def get_filtered_supported_project_types(
     """
     Return possible project types based on CVS-105432, excluding cross-mapping projects.
 
-    Project mapping is different based on the dataset format.
+    Project mapping is different based on the dataset format. (CVS-105432)
     For Geti-exported Datumaro format:
-      candaidates should be the task type itself (+ cross-mapping projects).
+      candidates should be the task type itself (+ cross-mapping projects).
     For public formats(coco, voc, yolo) + Datumaro format not exported from Geti:
       candidate tasks would be decided based on annotation types.
       - label -> classification
       - bbox -> detection
-      - polygon/ellipse/mask -> segmentation.
+      - polygon/ellipse/mask -> segmentation
+      - points -> keypoint detection
+
+    :param dm_infos: datumaro dataset info
+    :param label_to_ann_types: mapping of labels in dataset to their ann_type
+    :return: A list of supported Geti project types
     """
     exported_project_type = ImportUtils.get_exported_project_type(dm_infos)
     if exported_project_type != GetiProjectType.UNKNOWN:
@@ -643,23 +635,16 @@ def get_project_metas_with_labels(
     Get mapping of domains to label names in the dataset. The list of labels for the
     domain will be filled with the labels which are compatible with the domain.
 
-    :param dm_dataset: datumaro dataset
+    :param dm_infos: datumaro dataset info
+    :param dm_categories: datumaro dataset categories
+    :param label_to_ann_types: mapping of labels in dataset to their ann_type
     :return: A list containing a dictionary for each supported task with their
-    compatible labels, list of possible domains in dataset based on present
-    annotation types
+        compatible labels, list of possible domains in dataset based on present
+        annotation types
     """
-
-    # Project mapping is different based on the dataset format. (CVS-105432)
-    # For Geti-exported Datumaro format:
-    #   candaidates should be the task type itself + cross-mapping projects.
-    # For public formats(coco, voc, yolo) + Datumaro format not exported from Geti:
-    #   candidate tasks would be decided based on annotation types.
-    #   - label -> classification
-    #   - bbox -> detection
-    #   - polygon/ellipse/mask -> segmentation.
-
     filtered_supported_project_types = get_filtered_supported_project_types(
-        dm_infos=dm_infos, label_to_ann_types=label_to_ann_types
+        dm_infos=dm_infos,
+        label_to_ann_types=label_to_ann_types,
     )
 
     # Extract project meta-data that will be utilized when build a REST API response
@@ -686,7 +671,7 @@ def get_project_metas_with_labels(
                 f"{ImportUtils.project_type_to_rest_api_string(project_type)}: {e}"
             )
 
-    # Re-map project_type for hierarchical classifcation task.
+    # Re-map project_type for hierarchical classification task.
     # Note that single-label/multi-label/hierarchical classification project has the same project_type in Geti.
     # But we should distinguish hierarchical classification on REST API
     for project_meta in project_metas_with_labels:
diff --git a/interactive_ai/workflows/geti_domain/dataset_ie/tests/fixtures/datasets.py b/interactive_ai/workflows/geti_domain/dataset_ie/tests/fixtures/datasets.py
index 3707586c3..175ef9f72 100644
--- a/interactive_ai/workflows/geti_domain/dataset_ie/tests/fixtures/datasets.py
+++ b/interactive_ai/workflows/geti_domain/dataset_ie/tests/fixtures/datasets.py
@@ -773,7 +773,7 @@ def get_dataset_info(fxt_dataset_id_str: str) -> DatasetInfo:
                 "left_ankle",  # 16
                 "right_ankle",  # 17
             }
-            keypoint_structure = {
+            keypoint_structure: dict[str, list] = {
                 "edges": [
                     {"nodes": ["left_shoulder", "left_hip"]},  # [6,12]
                     {"nodes": ["left_ear", "left_shoulder"]},  # [4,6]
@@ -795,7 +795,25 @@ def get_dataset_info(fxt_dataset_id_str: str) -> DatasetInfo:
                     {"nodes": ["left_eye", "right_eye"]},  # [2,3]
                     {"nodes": ["left_ankle", "left_knee"]},  # [16,14]
                 ],
-                "positions": [],  # TODO CVS-156570
+                "positions": [
+                    {"label": "nose", "x": 0.1, "y": 0.4},
+                    {"label": "left_eye", "x": 0.2, "y": 0.5},
+                    {"label": "right_eye", "x": 0.3, "y": 0.6},
+                    {"label": "left_ear", "x": 0.4, "y": 0.7},
+                    {"label": "right_ear", "x": 0.5, "y": 0.8},
+                    {"label": "left_shoulder", "x": 0.6, "y": 0.9},
+                    {"label": "right_shoulder", "x": 0.7, "y": 1.0},
+                    {"label": "left_elbow", "x": 0.8, "y": 0.9},
+                    {"label": "right_elbow", "x": 0.9, "y": 0.8},
+                    {"label": "left_wrist", "x": 1.0, "y": 0.7},
+                    {"label": "right_wrist", "x": 0.9, "y": 0.6},
+                    {"label": "left_hip", "x": 0.8, "y": 0.5},
+                    {"label": "right_hip", "x": 0.7, "y": 0.4},
+                    {"label": "left_knee", "x": 0.6, "y": 0.3},
+                    {"label": "right_knee", "x": 0.5, "y": 0.2},
+                    {"label": "left_ankle", "x": 0.4, "y": 0.1},
+                    {"label": "right_ankle", "x": 0.3, "y": 0.0},
+                ],
             }
             return DatasetInfo(
                 exported_project_type=GetiProjectType.KEYPOINT_DETECTION,
diff --git a/interactive_ai/workflows/geti_domain/dataset_ie/tests/fixtures/projects.py b/interactive_ai/workflows/geti_domain/dataset_ie/tests/fixtures/projects.py
index 5d030bd50..69066a970 100644
--- a/interactive_ai/workflows/geti_domain/dataset_ie/tests/fixtures/projects.py
+++ b/interactive_ai/workflows/geti_domain/dataset_ie/tests/fixtures/projects.py
@@ -9,6 +9,7 @@
 from geti_types import ID
 from iai_core.algorithms import ModelTemplateList
 from iai_core.entities.color import Color
+from iai_core.entities.keypoint_structure import KeypointEdge, KeypointPosition, KeypointStructure
 from iai_core.entities.label import Domain, Label
 from iai_core.entities.label_schema import LabelGroup, LabelGroupType, LabelSchema, LabelSchemaView
 from iai_core.entities.model_template import HyperParameterData, InstantiationType, ModelTemplate, TaskFamily, TaskType
@@ -22,6 +23,7 @@
 from tests.test_helpers import (
     generate_ellipse_shape,
     generate_images_and_annotation_scenes,
+    generate_keypoint_shape,
     generate_polygon_shape,
     generate_random_video,
     generate_rectangle_shape,
@@ -743,3 +745,46 @@ def fxt_label_schema_classification() -> LabelSchema:
             ),
         ],
     )
+
+
+@pytest.fixture
+def fxt_keypoint_detection_project(request) -> Project:
+    name = "_test_keypoint_project"
+    model_template_id = "keypoint_detection"
+    register_model_template(request, type(None), model_template_id, trainable=True, task_type="KEYPOINT_DETECTION")
+
+    edges = []
+    positions = []
+    edges.append(KeypointEdge(node_1=ID("rectangle"), node_2=ID("ellipse")))
+    edges.append(KeypointEdge(node_1=ID("ellipse"), node_2=ID("triangle")))
+    positions.append(KeypointPosition(node=ID("rectangle"), x=0.3, y=0.3))
+    positions.append(KeypointPosition(node=ID("ellipse"), x=0.4, y=0.4))
+    positions.append(KeypointPosition(node=ID("triangle"), x=0.5, y=0.5))
+    keypoint_structure = KeypointStructure(edges=edges, positions=positions)
+
+    project = ProjectFactory.create_project_single_task(
+        name=name,
+        description=name,
+        creator_id="",
+        labels=[
+            {"name": "rectangle", "color": "#00ff00ff"},
+            {"name": "ellipse", "color": "#0000ffff"},
+            {"name": "triangle", "color": "#ff0000ff"},
+        ],
+        model_template_id=model_template_id,
+        keypoint_structure=keypoint_structure,
+    )
+    labels = get_project_labels(project)
+
+    generate_images_and_annotation_scenes(
+        project=project,
+        num_annotated_images=10,
+        num_unannotated_images=2,
+        labels=labels,
+        shape_generator=generate_keypoint_shape,
+    )
+
+    generate_random_video(project=project, video_name="Annotated Video", generate_annotations=True)
+    generate_random_video(project=project, video_name="Unannotated Video", generate_annotations=False)
+
+    return project
diff --git a/interactive_ai/workflows/geti_domain/dataset_ie/tests/integration/test_export_management.py b/interactive_ai/workflows/geti_domain/dataset_ie/tests/integration/test_export_management.py
index 0601c9a99..e7769383e 100644
--- a/interactive_ai/workflows/geti_domain/dataset_ie/tests/integration/test_export_management.py
+++ b/interactive_ai/workflows/geti_domain/dataset_ie/tests/integration/test_export_management.py
@@ -46,6 +46,7 @@ def setup_class(self):
             ("anom_class", "datumaro"): self._assert_datumaro_export_valid,
             ("anom_seg", "datumaro"): self._assert_datumaro_export_valid,
             ("anom_det", "datumaro"): self._assert_datumaro_export_valid,
+            ("keypoint", "datumaro"): self._assert_datumaro_export_valid,
         }
 
     @patch("jobs_common.tasks.utils.secrets.set_env_vars", new=return_none)
@@ -69,6 +70,7 @@ def setup_class(self):
             ("fxt_annotated_anomaly_cls_project_with_video", "anom_class", "datumaro"),
             ("fxt_annotated_anomaly_det_project", "anom_det", "datumaro"),
             ("fxt_annotated_anomaly_seg_project", "anom_seg", "datumaro"),
+            ("fxt_annotated_keypoint_det_project", "keypoint", "datumaro"),
         ],
     )
     def test_export_projects(
diff --git a/interactive_ai/workflows/geti_domain/dataset_ie/tests/integration/test_parse_dataset_new_project.py b/interactive_ai/workflows/geti_domain/dataset_ie/tests/integration/test_parse_dataset_new_project.py
index dc18b8453..b6eeb8e1c 100644
--- a/interactive_ai/workflows/geti_domain/dataset_ie/tests/integration/test_parse_dataset_new_project.py
+++ b/interactive_ai/workflows/geti_domain/dataset_ie/tests/integration/test_parse_dataset_new_project.py
@@ -283,7 +283,25 @@ def test_parse_dataset_for_import_to_new_project__datumaro_format__keypoint_dete
                 {"nodes": ["left_eye", "right_eye"]},  # [2,3]
                 {"nodes": ["left_ankle", "left_knee"]},  # [16,14]
             ],
-            "positions": [],  # TODO CVS-156570
+            "positions": [
+                {"label": "nose", "x": 0.1, "y": 0.4},
+                {"label": "left_eye", "x": 0.2, "y": 0.5},
+                {"label": "right_eye", "x": 0.3, "y": 0.6},
+                {"label": "left_ear", "x": 0.4, "y": 0.7},
+                {"label": "right_ear", "x": 0.5, "y": 0.8},
+                {"label": "left_shoulder", "x": 0.6, "y": 0.9},
+                {"label": "right_shoulder", "x": 0.7, "y": 1.0},
+                {"label": "left_elbow", "x": 0.8, "y": 0.9},
+                {"label": "right_elbow", "x": 0.9, "y": 0.8},
+                {"label": "left_wrist", "x": 1.0, "y": 0.7},
+                {"label": "right_wrist", "x": 0.9, "y": 0.6},
+                {"label": "left_hip", "x": 0.8, "y": 0.5},
+                {"label": "right_hip", "x": 0.7, "y": 0.4},
+                {"label": "left_knee", "x": 0.6, "y": 0.3},
+                {"label": "right_knee", "x": 0.5, "y": 0.2},
+                {"label": "left_ankle", "x": 0.4, "y": 0.1},
+                {"label": "right_ankle", "x": 0.3, "y": 0.0},
+            ],
         }
         if fxt_keypoint_detection:
             dataset_info = DatasetInfo(
diff --git a/interactive_ai/workflows/geti_domain/dataset_ie/tests/test_helpers.py b/interactive_ai/workflows/geti_domain/dataset_ie/tests/test_helpers.py
index 6f192a7b2..3b9b7b69d 100644
--- a/interactive_ai/workflows/geti_domain/dataset_ie/tests/test_helpers.py
+++ b/interactive_ai/workflows/geti_domain/dataset_ie/tests/test_helpers.py
@@ -195,6 +195,15 @@ def generated_rotated_rectangle_shape() -> Polygon:
     return Polygon(points=points)
 
 
+def generate_keypoint_shape() -> Keypoint:
+    """
+    Generate keypoint shape
+
+    :return: polygon entity
+    """
+    return Keypoint(x=0.2, y=0.3, is_visible=True)
+
+
 def generate_images_and_annotation_scenes(
     project: Project,
     num_annotated_images: int,
diff --git a/interactive_ai/workflows/geti_domain/dataset_ie/uv.lock b/interactive_ai/workflows/geti_domain/dataset_ie/uv.lock
index 897c65613..6ae07e3ea 100644
--- a/interactive_ai/workflows/geti_domain/dataset_ie/uv.lock
+++ b/interactive_ai/workflows/geti_domain/dataset_ie/uv.lock
@@ -642,7 +642,7 @@ dev = [
 
 [[package]]
 name = "datumaro"
-version = "1.8.0"
+version = "1.10.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "attrs" },
@@ -663,6 +663,7 @@ dependencies = [
     { name = "ovmsclient" },
     { name = "pandas" },
     { name = "pillow" },
+    { name = "portalocker" },
     { name = "protobuf" },
     { name = "pyarrow" },
     { name = "pycocotools" },
@@ -680,11 +681,11 @@ dependencies = [
     { name = "tritonclient", extra = ["all"] },
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/12/7c/0d29f21a68e9e1543f87cb78213e5870f499cf28bee850fa519ba491e31a/datumaro-1.8.0.tar.gz", hash = "sha256:2a8ef4bd36f968ded6b6f4f56fe974431cd7bd4d1e3d9f75e447b1c928fa1dbc", size = 564692 }
+sdist = { url = "https://files.pythonhosted.org/packages/50/62/a915845b2d650ec2e2dc9f07716872228f898ff4ee7c45a729304295b3b7/datumaro-1.10.0.tar.gz", hash = "sha256:408a07fb4c74a2d832d4493c9c8001283cc0f40b02fdddc26b9e05ffb6ee8477", size = 567726 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/04/a0/ada181dd1cb3d05f88ef24e6eb39c30e0065cfc27758f2c404fdcb715b9c/datumaro-1.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:74a4f3f5a0acecb331c91a4eac2127bf28fea90ece75fc98a51f81eaa65d8a4a", size = 1137441 },
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+    { url = "https://files.pythonhosted.org/packages/46/62/3bb463635ebac05b2603416e7c79e56ac6af7c401056246ab448dc09c8f8/datumaro-1.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1e7cee5d990cf85c246e33b8dfe21a67298fbb2a8886aa5607d97924087a0b97", size = 1167120 },
+    { url = "https://files.pythonhosted.org/packages/fc/a1/3aa0975be54a51480f83a6f7315e2d6dc31b1b446847faa4cc34589db2f8/datumaro-1.10.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:d2f41647ed54bb09ca306614203ae90f69e65e89e18d7c36ed0f75c69278ee6a", size = 1682767 },
+    { url = "https://files.pythonhosted.org/packages/84/46/035835142298a8eacea7bdc19a7b0949a7d5d33a480814666741c39a63ba/datumaro-1.10.0-cp310-cp310-win_amd64.whl", hash = "sha256:2823e930c1e4ca2c75046354d6214401498eff5f3c27c63d7a62d84958be56d5", size = 981121 },
 ]
 
 [[package]]
@@ -2307,19 +2308,20 @@ wheels = [
 
 [[package]]
 name = "orjson"
-version = "3.10.5"
+version = "3.10.7"
 source = { registry = "https://pypi.org/simple" }
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index 5e9803312..17838cc32 100644
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index fa4e1e14e..09d87ef2a 100644
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diff --git a/interactive_ai/workflows/geti_domain/project_ie/uv.lock b/interactive_ai/workflows/geti_domain/project_ie/uv.lock
index 4b466c968..3d64d4f5f 100644
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diff --git a/interactive_ai/workflows/geti_domain/train/uv.lock b/interactive_ai/workflows/geti_domain/train/uv.lock
index 21b487da9..e221dc27a 100644
--- a/interactive_ai/workflows/geti_domain/train/uv.lock
+++ b/interactive_ai/workflows/geti_domain/train/uv.lock
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     { name = "pandas" },
     { name = "pillow" },
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