VI-RGBT1500 Dataset and MGAI_TCSVT2022
Multiple Graph Affinity Interactive Network and A Variable Illumination Dataset for RGBT Image Salient Object Detection, IEEE Transactions on Circuits and Systems for Video Technology, 2022, doi:10.1109/TCSVT.2022.3233131. Paper
Update:
- 2023/06/06-We update the MGAI code.
- 2023/04/17-We fix four wrong T images. Please use the latest dataset.
VI-RGBT1500 Dataset:
- We provide the dataset of VI-RGBT1500:
- VI-RGBT1500: Baidu Cloud, Password: pzit; Google Cloud.
- Different Illumination for VI-RGBT1500: Baidu Cloud, Password: zg1v; Google Cloud.
- We provide the dataset of VI-RGBT Training-set:
- VI-RGBT Training-set: Baidu Cloud, Password: 9c7v; Google Cloud.
Results of MGAI:
- We provide the resutls of our MGAI on VI-RGBT1500:
- Saliency maps of our MGAI on VI-RGBT1500 trained on VI-RGBT Training-set: Baidu Cloud, Password: da85; Google Cloud.
- Saliency maps of our MGAI on VI-RGBT1500 trained on VT5000: Baidu Cloud, Password: jij3; Google Cloud.
- We provide the resutls of our MGAI on VT821, VT1000, and VT5000:
- Saliency maps of our MGAI on VT821, VT1000, VT5000 trained on VT5000: Baidu Cloud, Password: dfhy; Google Cloud.
Results of MGFL and LTCR:
- We provide the resutls of our MGFL and LTCR on VI-RGBT1500, VT821, VT1000, and VT5000:
- Saliency maps of our MGFL and LTCR on VI-RGBT1500, VT821, VT1000, and VT5000: Baidu Cloud, Password: k0un; Google Cloud.
If you find our VI-RGBT1500 dataset and MGAI useful, please cite our papers:
@ARTICLE{10003255,
author={Song, Kechen and Huang, Liming and Gong, Aojun and Yan, Yunhui},
journal={IEEE Transactions on Circuits and Systems for Video Technology},
title={Multiple Graph Affinity Interactive Network and a Variable Illumination Dataset for RGBT Image Salient Object Detection},
year={2023}, volume={33}, number={7}, pages={3104-3118},
doi={10.1109/TCSVT.2022.3233131}}
@ARTICLE{9389777,
author={Huang, Liming and Song, Kechen and Wang, Jie and Niu, Menghui and Yan, Yunhui},
journal={IEEE Transactions on Circuits and Systems for Video Technology},
title={Multi-Graph Fusion and Learning for RGBT Image Saliency Detection},
year={2022}, volume={32}, number={3}, pages={1366-1377},
doi={10.1109/TCSVT.2021.3069812}}
@ARTICLE{9184226,
author={Huang, Liming and Song, Kechen and Gong, Aojun and Liu, Chuang and Yan, Yunhui},
journal={IEEE Signal Processing Letters},
title={RGB-T Saliency Detection via Low-Rank Tensor Learning and Unified Collaborative Ranking},
year={2020}, volume={27}, number={}, pages={1585-1589},
doi={10.1109/LSP.2020.3020735}}
Contact Us:
If you have any questions, please contact Liming Huang (huanglm.me@gmail.com). Many thanks.