├── GraphNet .pdf ├── voc_result.png ├── illustration.png ├── context_result.png └── README.md /GraphNet .pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MengyangPu/GraphNet/HEAD/GraphNet .pdf -------------------------------------------------------------------------------- /voc_result.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MengyangPu/GraphNet/HEAD/voc_result.png -------------------------------------------------------------------------------- /illustration.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MengyangPu/GraphNet/HEAD/illustration.png -------------------------------------------------------------------------------- /context_result.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MengyangPu/GraphNet/HEAD/context_result.png -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # GraphNet 2 | GraphNet: Learning Image Pseudo Annotations for Weakly-Supervised Semantic Segmentation, in ACM Multimedia 2018 (oral) [[Paper]](https://github.com/MengyangPu/GraphNet/blob/master/GraphNet%20.pdf) 3 | 4 | ## Overview 5 | ![Illustration](illustration.png) 6 | 7 | ### Implementation Details 8 | The network architecture of [DeepLabv2-VGG16](https://github.com/TheLegendAli/DeepLab-Context2) serves as our network architecture of scribble and bounding box annotations experiments. 9 | 10 | ### Results 11 | > #### Results on the PASCAL VOC 2012 dataset 12 | method | annotation | w/o CRF | w/ CRF 13 | --------------------------- | ------------- | ------------- | ------------- 14 | Ours: ScrGraphNet, Initial | scribble | 63.3 | 68.2 15 | Ours: ScrGraphNet, 1-Round | scribble | 64.5 | 68.9 16 | Ours: BboxGraphNet, Initial | bounding box | 57.1 | 63.4 17 | Ours: BboxGraphNet, 1-Round | bounding box | 61.3 | 65.6 18 | 19 | ![VOC Segmentation](voc_result.png) 20 | > #### Results on the PASCAL-CONTEXT dataset 21 | method | w/o CRF | w/ CRF 22 | --------------------------- | ------------- | ------------- 23 | Ours: ScrGraphNet, Initial | 33.1 | 39.7 24 | Ours: ScrGraphNet, 1-Round | 33.9 | 40.2 25 | 26 | ![CONTEXT Segmentation](context_result.png) 27 | 28 | ## Citation 29 | If you find the paper useful for your research, please cite: 30 | ```bibtex 31 | @INPROCEEDINGS{Pu2018GraphNet, 32 | author = {Pu, Mengyang and Huang, Yaping and Guan, Qingji and Zou, Qi}, 33 | title = {GraphNet: Learning Image Pseudo Annotations for Weakly-Supervised Semantic Segmentation}, 34 | booktitle = {ACM Multimedia}, 35 | year = {2018} 36 | } 37 | ``` 38 | --------------------------------------------------------------------------------