Skip to content
/ UniA Public

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

Notifications You must be signed in to change notification settings

zwyang6/UniA

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

15 Commits
 
 
 
 
 
 

Repository files navigation

Tackling Ambiguity from Perspective of Uncertainty Inference and Affinity Diversification for Weakly Supervised Semantic Segmentation arXiv

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 zwyang21@m.fudan.edu.cn.

Overview

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

UniA pipeline

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

UniA 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}
}

About

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

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published