Self-supervised learning for RGB-D object tracking
-
Published:2024-11
Issue:
Volume:155
Page:110543
-
ISSN:0031-3203
-
Container-title:Pattern Recognition
-
language:en
-
Short-container-title:Pattern Recognition
Author:
Zhu Xue-FengORCID,
Xu Tianyang,
Atito Sara,
Awais Muhammad,
Wu Xiao-Jun,
Feng Zhenhua,
Kittler Josef
Reference39 articles.
1. Deep visual tracking: Review and experimental comparison;Li;Pattern Recognit.,2018
2. Transformer-based visual object tracking via fine–coarse concatenated attention and cross concatenated MLP;Gao;Pattern Recognit.,2024
3. The tenth visual object tracking vot2022 challenge results;Kristan,2022
4. S. Song, J. Xiao, Tracking revisited using RGBD camera: Unified benchmark and baselines, in: Proceedings of the IEEE International Conference on Computer Vision, 2013, pp. 233–240.
5. A. Lukezic, U. Kart, J. Kapyla, A. Durmush, J.-K. Kamarainen, J. Matas, M. Kristan, Cdtb: A color and depth visual object tracking dataset and benchmark, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, 2019, pp. 10013–10022.