3 papers
cs.CV2025
What You Have is What You Track: Adaptive and Robust Multimodal Tracking
Yuedong Tan, Jiawei Shao, Eduard Zamfir +7
Multimodal data is known to be helpful for visual tracking by improving robustness to appearance variations. However, sensor synchronization challenges often compromise data availa…
cs.CV2024
Heterogeneous Graph Transformer for Multiple Tiny Object Tracking in RGB-T Videos
Qingyu Xu, Longguang Wang, Weidong Sheng +4
Tracking multiple tiny objects is highly challenging due to their weak appearance and limited features. Existing multi-object tracking algorithms generally focus on single-modality…
cs.CV2024
XTrack: Multimodal Training Boosts RGB-X Video Object Trackers
Yuedong Tan, Zongwei Wu, Yuqian Fu +7
Multimodal sensing has proven valuable for visual tracking, as different sensor types offer unique strengths in handling one specific challenging scene where object appearance vari…