[CVPR2024] Separate and Conquer: Decoupling Co-occurrence via Decomposition and Representation for Weakly Supervised Semantic Segmentation 
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Mar. 21st, 2024: All Codes, logs, and checkpoints are available now🔥🔥🔥- If you have any questions, please feel free to leave issues or contact us by zwyang21@m.fudan.edu.cn.
We proposed a Separate and Conquer philosophy to effectively tackle the co-occurrence issue in WSSS.
wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tarThe augmented annotations are from SBD dataset. The download link of the augmented annotations at
DropBox. After downloading SegmentationClassAug.zip, you should unzip it and move it to VOCdevkit/VOC2012/.
VOCdevkit/
└── VOC2012
├── Annotations
├── ImageSets
├── JPEGImages
├── SegmentationClass
├── SegmentationClassAug
└── SegmentationObjectwget http://images.cocodataset.org/zips/train2014.zip
wget http://images.cocodataset.org/zips/val2014.zipTo generate VOC style segmentation labels for COCO, you could use the scripts provided at this repo, or just download the generated masks from Google Drive.
COCO/
├── JPEGImages
│ ├── train2014
│ └── val2014
└── SegmentationClass
├── train2014
└── val2014Please refer to the requirements.txt.
We incorporate a regularization loss for segmentation. Please refer to the instruction for this python extension.
### train voc
bash run_train.sh scripts/train_voc.py [gpu_number] [master_port] [gpu_device] train_voc
### train coco
bash run_train.sh scripts/train_coco.py [gpu_numbers] [master_port] [gpu_devices] train_coco### eval voc
bash run_evaluate_seg_voc.sh tools/infer_seg_voc.py [gpu_device] [checkpoint_path]
### eval coco
bash run_evaluate_seg_coco.sh tools/infer_seg_coco.py [gpu_number] [master_port] [gpu_device] [checkpoint_path]Semantic performance on VOC and COCO. Logs and weights are available now.
| Dataset | Backbone | Val | Test | Log | Weight |
|---|---|---|---|---|---|
| PASCAL VOC | ViT-B | 74.0 | 73.8 | log | weight |
| MS COCO | ViT-B | 46.7 | - | log | weight |
Please cite our work if you find it helpful to your reseach. 💕
@InProceedings{Yang_2024_CVPR,
author = {Yang, Zhiwei and Fu, Kexue and Duan, Minghong and Qu, Linhao and Wang, Shuo and Song, Zhijian},
title = {Separate and Conquer: Decoupling Co-occurrence via Decomposition and Representation for Weakly Supervised Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2024},
pages = {3606-3615}
}This repo is built upon ToCo, DINO, and SupCon. Many thanks to their brilliant works!!!