3 papers
cs.CV2025
Less is More: Token Context-aware Learning for Object Tracking
Chenlong Xu, Bineng Zhong, Qihua Liang +3
Recently, several studies have shown that utilizing contextual information to perceive target states is crucial for object tracking. They typically capture context by incorporating…
cs.CV2024
MambaLCT: Boosting Tracking via Long-term Context State Space Model
Xiaohai Li, Bineng Zhong, Qihua Liang +3
Effectively constructing context information with long-term dependencies from video sequences is crucial for object tracking. However, the context length constructed by existing wo…
cs.CV2024
Robust Tracking via Mamba-based Context-aware Token Learning
Jinxia Xie, Bineng Zhong, Qihua Liang +3
How to make a good trade-off between performance and computational cost is crucial for a tracker. However, current famous methods typically focus on complicated and time-consuming…