[CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision

Related tags

Deep Learningsemi-supervised-learningsemantic-segmentationcvpr2021semi-supervised-segmentation
Overview

TorchSemiSeg


[CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision

by Xiaokang Chen1, Yuhui Yuan2, Gang Zeng1, Jingdong Wang2.

1 Key Laboratory of Machine Perception (MOE), Peking University 2 Microsoft Research Asia.

[Poster] [Video (YouTube)]

Simpler Is Better !


News

  • [June 3 2021] Please check our paper in Arxiv. Data and code have been released.

Installation

Please refer to the Installation document.

Getting Started

Please follow the Getting Started document.

Citation

Please consider citing this project in your publications if it helps your research.

@inproceedings{chen2021-CPS,
  title={Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision},
  author={Chen, Xiaokang and Yuan, Yuhui and Zeng, Gang and Wang, Jingdong},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2021}
}

TODO

  • Dataset release
  • Code for CPS + CutMix
  • Code for Cityscapes dataset
  • Other SOTA semi-supervised segmentation methods
Owner
Chen XiaoKang
Master student at Peking University, Computer Vision Explorer
Chen XiaoKang
GitHub Repository
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