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Official PyTorch implementation of "Quality-Aware RGBT Tracking via Supervised Reliability Learning and Weighted Residual Guidance". (ACM MM 2023)

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Quality-Aware RGBT Tracking via Supervised Reliability Learning and Weighted Residual Guidance

Citation

If you're using this code in a publication, please cite our paper.

@inproceedings{liu2023quality,
              title={Quality-Aware RGBT Tracking via Supervised Reliability Learning and Weighted Residual Guidance},
              author={Liu, Lei and Li, Chenglong and Xiao, Yun and Tang, Jin},
              booktitle={Proceedings of the ACM International Conference on Multimedia},
              pages={3129--3137},
              year={2023}
            }

System Requirements are the same as DiMP.

Pretrained Model and results If you only run the tracker, you can use the pretrained model: Google Drive/Baidu Yun. Also, results from pretrained model are provided in Google Drive/Baidu Yun.

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Official PyTorch implementation of "Quality-Aware RGBT Tracking via Supervised Reliability Learning and Weighted Residual Guidance". (ACM MM 2023)

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