diff --git a/README.md b/README.md index 3760de0..e2df83a 100644 --- a/README.md +++ b/README.md @@ -1,10 +1,14 @@ -# [PseudoSeg: Designing Pseudo Labels for Semantic Segmentation](https://arxiv.org/pdf/2010.09713v1.pdf) +# PseudoSeg: Designing Pseudo Labels for Semantic Segmentation + +Official Tensorflow implementation for [PseudoSeg: Designing Pseudo Labels for Semantic Segmentation (ICLR 2021)](https://arxiv.org/pdf/2010.09713.pdf). PseudoSeg is a simple consistency training framework for semi-supervised image semantic segmentation, which has a simple and novel re-design of pseudo-labeling to generate well-calibrated structured pseudo labels for training with unlabeled or weakly-labeled data. It is implemented by [Yuliang Zou](https://yuliang.vision/) (research intern) in 2020 Summer. +See the [project page](https://yuliang.vision/pseudo_seg/) for more details. + __This is not an official Google product.__ ## Instruction @@ -153,10 +157,10 @@ python vis.py \ If you use this work for your research, please cite our paper. ``` -@article{zou2020pseudoseg, +@inproceedings{zou2021pseudoseg, title={PseudoSeg: Designing Pseudo Labels for Semantic Segmentation}, author={Zou, Yuliang and Zhang, Zizhao and Zhang, Han and Li, Chun-Liang and Bian, Xiao and Huang, Jia-Bin and Pfister, Tomas}, - journal={International Conference on Learning Representations (ICLR)}, + booktitle={International Conference on Learning Representations (ICLR)}, year={2021} } ``` diff --git a/data_splits/pascal_voc_seg/2_clean.txt b/data_splits/pascal_voc_seg/2_clean.txt new file mode 100644 index 0000000..9380cc9 --- /dev/null +++ b/data_splits/pascal_voc_seg/2_clean.txt @@ -0,0 +1,732 @@ +2007_006066 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