The following is a set of baseline results from different methods. These results were obtained without using the training set. Only the first frame of the each testing sequence was used to estimate key parameters if needed. Please refer to [1] for details. Please refer to the contest page for related codes.
| False-color/Hyperspectral videos | ||
|---|---|---|
| Tracker | AUC | DP@20pixels |
| MMF-Net [1] | 0.5266 | 0.6826 |
| ViPT [2] | 0.5764 | 0.7391 |
| TransDAT [3] | 0.4532 | 0.5866 |
| SPIRIT [4] | 0.4177 | 0.5336 |
| SEE-Net [5] | 0.4257 | 0.6070 |
| HELIOS [6] | 0.5770 | 0.7281 |
[1] Z. Li, F. Xiong, J. Zhou, J. Lu, Z. Zhao and Y. Qian, "Material-Guided Multiview Fusion Network for Hyperspectral Object Tracking," IEEE Transactions on Geoscience and Remote Sensing, vol. code Results
[2] Zhu J, Lai S, Chen X, et al. Visual prompt multi-modal tracking[C]//Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2023: 9516-9526. code Results
[3] Y. Wu, L. Jiao, X. Liu, F. Liu, S. Yang and L. Li, "Domain Adaptation-aware Transformer for Hyperspectral Object Tracking," in IEEE Transactions on Circuits and Systems for Video Technology. code Results
[4] Y. Chen, Q. Yuan, Y. Tang, Y. Xiao, J. He and L. Zhang, "SPIRIT: Spectral Awareness Interaction Network With Dynamic Template for Hyperspectral Object Tracking," in IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-16, 2024. code Results
[5] Z. Li, F. Xiong, J. Zhou, J. Lu and Y. Qian, "Learning a Deep Ensemble Network With Band Importance for Hyperspectral Object Tracking," in IEEE Transactions on Image Processing, vol. 32, pp. 2901-2914, 2023, doi: 10.1109/TIP.2023.3263109. code Results
[6] R. Muszyński and H. Luong, "Helios: Hyperspectral Hindsight Ostracker," 2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Athens, Greece, 2023, pp. 1-5, doi: 10.1109/WHISPERS61460.2023.10430711. code Results