3 citations · 4 across the 8 of their papers we have counts for
8 papers
An Efficient Token Compression Framework for Visual Object Tracking
Weijing Wu, Qihua Liang, Bineng Zhong +3
Refining visual representations by eliminating their internal feature-level redundancy is crucial for simultaneously optimizing the performance and computational cost of models in…
UBATrack: Spatio-Temporal State Space Model for General Multi-Modal Tracking
Qihua Liang, Liang Chen, Yaozong Zheng +3
Multi-modal object tracking has attracted considerable attention by integrating multiple complementary inputs (e.g., thermal, depth, and event data) to achieve outstanding performa…
Dynamic Updates for Language Adaptation in Visual-Language Tracking
Xiaohai Li, Bineng Zhong, Qihua Liang +3
The consistency between the semantic information provided by the multi-modal reference and the tracked object is crucial for visual-language (VL) tracking. However, existing VL tra…
Adaptive Perception for Unified Visual Multi-modal Object Tracking
Xiantao Hu, Bineng Zhong, Qihua Liang +4
Recently, many multi-modal trackers prioritize RGB as the dominant modality, treating other modalities as auxiliary, and fine-tuning separately various multi-modal tasks. This imba…
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…
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…
Autoregressive Queries for Adaptive Tracking with Spatio-TemporalTransformers
Jinxia Xie, Bineng Zhong, Zhiyi Mo +4
The rich spatio-temporal information is crucial to capture the complicated target appearance variations in visual tracking. However, most top-performing tracking algorithms rely on…
ODTrack: Online Dense Temporal Token Learning for Visual Tracking
Yaozong Zheng, Bineng Zhong, Qihua Liang +3
Online contextual reasoning and association across consecutive video frames are critical to perceive instances in visual tracking. However, most current top-performing trackers per…