Awesome
TorchSemiSeg
<br><br>[CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision
by Xiaokang Chen<sup>1</sup>, Yuhui Yuan<sup>2</sup>, Gang Zeng<sup>1</sup>, Jingdong Wang<sup>2</sup>.
<sup>1</sup> Key Laboratory of Machine Perception (MOE), Peking University <sup>2</sup> Microsoft Research Asia.
Simpler Is Better !
<img src=ReadmePic/cps.png width="600">
News
- [July 9 2021] We have released some SOTA methods (Mean Teacher, CCT, GCT).
- [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