[TMM2025] Tackling Ambiguity from Perspective of Uncertainty Inference and Affinity Diversification for Weakly Supervised Semantic Segmentation

News

• Code will be public very soon Once UniA is accepted. 🔥🔥🔥
• Don't hesitate to give us a 🌟 for updation!
• If you have any questions, please feel free to leave issues or contact us by [email protected].

Overview

We proposed UniA, an unified single-stage framework, to tackle the ambiguity issue in WSSS.

Main Results

• Quantitative Results

Semantic performance on VOC and COCO. Logs are available now.

Dataset	Backbone	Val	Test	Log	Weight
PASCAL VOC	ViT-B	74.1	73.6	log	weight
MS COCO	ViT-B	43.2	-	log	weight

• Qualitative Results

Citation

Please cite our work if you find it helpful to your reseach. 💕

@article{yang2024tackling,
  title={Tackling Ambiguity from Perspective of Uncertainty Inference and Affinity Diversification for Weakly Supervised Semantic Segmentation},
  author={Yang, Zhiwei and Meng, Yucong and Fu, Kexue and Wang, Shuo and Song, Zhijian},
  journal={arXiv preprint arXiv:2404.08195},
  year={2024}
}