Awesome
Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection (GCAGC-CVPR2020)
Pipeline
Testing code
- python test.py
Pretrained models (HRNET version)
- Baidu Cloud Fetchcode: isrw && Google Cloud
Training Dataset (COCO-SEG, 78 categories, 200K images) && Cosal results
- Baidu Cloud Fetchcode: rbbj
- Baidu Cloud Fetchcode: aqaw && Google Cloud
Instance co-segmentation and co-saliency (published in TMM)
- Here is our extended transaction paper https://ieeexplore.ieee.org/abstract/document/9337219/
- Instance co-saliency/segmentation maps: Baidu Cloud Fetchcodes: 05em
- Instance evaluation codes (Matlab): Baidu Cloud Fetchcodes: v1up
- Google Cloud: link
Citation
If you use this code, please cite our paper:
@inproceedings{zhang2020adaptive,
title={Adaptive graph convolutional network with attention graph clustering for co-saliency detection},
author={Zhang, Kaihua and Li, Tengpeng and Shen, Shiwen and Liu, Bo and Chen, Jin and Liu, Qingshan},
booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
pages={9050--9059},
year={2020}
}
@article{li2021image,
title={Image Co-saliency Detection and Instance Co-segmentation using Attention Graph Clustering based Graph Convolutional Network},
author={Li, Tengpeng and Zhang, Kaihua and Shen, Shiwen and Liu, Bo and Liu, Qingshan and Li, Zhu},
journal={IEEE Transactions on Multimedia},
year={2021},
publisher={IEEE}
}