diff --git a/eg3d/training/volumetric_rendering/renderer.py b/eg3d/training/volumetric_rendering/renderer.py
index a27aea61..382db021 100644
--- a/eg3d/training/volumetric_rendering/renderer.py
+++ b/eg3d/training/volumetric_rendering/renderer.py
@@ -36,6 +36,22 @@ def generate_planes():
                             [1, 0, 0],
                             [0, 1, 0]]], dtype=torch.float32)
 
+# def project_onto_planes(planes, coordinates):
+#     """
+#     Does a projection of a 3D point onto a batch of 2D planes,
+#     returning 2D plane coordinates.
+
+#     Takes plane axes of shape n_planes, 3, 3
+#     # Takes coordinates of shape N, M, 3
+#     # returns projections of shape N*n_planes, M, 2
+#     """
+#     N, M, C = coordinates.shape
+#     n_planes, _, _ = planes.shape
+#     coordinates = coordinates.unsqueeze(1).expand(-1, n_planes, -1, -1).reshape(N*n_planes, M, 3)
+#     inv_planes = torch.linalg.inv(planes).unsqueeze(0).expand(N, -1, -1, -1).reshape(N*n_planes, 3, 3)
+#     projections = torch.bmm(coordinates, inv_planes)
+#     return projections[..., :2]
+
 def project_onto_planes(planes, coordinates):
     """
     Does a projection of a 3D point onto a batch of 2D planes,
@@ -45,12 +61,22 @@ def project_onto_planes(planes, coordinates):
     # Takes coordinates of shape N, M, 3
     # returns projections of shape N*n_planes, M, 2
     """
-    N, M, C = coordinates.shape
-    n_planes, _, _ = planes.shape
-    coordinates = coordinates.unsqueeze(1).expand(-1, n_planes, -1, -1).reshape(N*n_planes, M, 3)
-    inv_planes = torch.linalg.inv(planes).unsqueeze(0).expand(N, -1, -1, -1).reshape(N*n_planes, 3, 3)
-    projections = torch.bmm(coordinates, inv_planes)
-    return projections[..., :2]
+    
+    # # ORIGINAL
+    # N, M, C = coordinates.shape
+    # xy_coords = coordinates[..., [0, 1]]
+    # xz_coords = coordinates[..., [0, 2]]
+    # zx_coords = coordinates[..., [2, 0]]
+    # return torch.stack([xy_coords, xz_coords, zx_coords], dim=1).reshape(N*3, M, 2)
+
+    # FIXED
+    N, M, _ = coordinates.shape
+    xy_coords = coordinates[..., [0, 1]]
+    yz_coords = coordinates[..., [1, 2]]
+    zx_coords = coordinates[..., [2, 0]]
+    return torch.stack([xy_coords, yz_coords, zx_coords], dim=1).reshape(N*3, M, 2)
+
+
 
 def sample_from_planes(plane_axes, plane_features, coordinates, mode='bilinear', padding_mode='zeros', box_warp=None):
     assert padding_mode == 'zeros'