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20242026
most citedAutoregressive Queries for Adaptive Tracking with Spatio-TemporalTransformers

3 citations · 4 across the 11 of their papers we have counts for

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11 papers

cs.CV2026

Dual-branch Distilled Transformer for Efficient Asymmetric UAV Tracking

Hongtao Yang, Bineng Zhong, Qihua Liang +4

Given the real-time demands of UAV tracking, many methods simplify the backbone to reduce computation, but this often weakens feature representation and degrades performance in com…

cs.CV2026

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…

cs.CV2026

Learning to Track Instance from Single Nature Language Description

Yaozong Zheng, Bineng Zhong, Qihua Liang +3

How to achieve vision-language (VL) tracking using natural language descriptions from a video sequence \textbf{without relying on any bounding-box ground truth}? In this work, we a…

cs.CV2026

Boosting Self-Supervised Tracking with Contextual Prompts and Noise Learning

Yaozong Zheng, Qihua Liang, Bineng Zhong +4

Learning robust contextual knowledge from unlabeled videos is essential for advancing self-supervised tracking. However, conventional self-supervised trackers lack effective contex…

cs.CV2025

Explicit Context Reasoning with Supervision for Visual Tracking

Fansheng Zeng, Bineng Zhong, Haiying Xia +4

Contextual reasoning with constraints is crucial for enhancing temporal consistency in cross-frame modeling for visual tracking. However, mainstream tracking algorithms typically a…

cs.CV2025

Exploring Decoupled Spatio-Temporal Consistency Learning and Self-Prompting Evolution for Self-Supervised Tracking

Yaozong Zheng, Bineng Zhong, Qihua Liang +4

The success of visual tracking has been largely driven by datasets with manual box annotations. However, these box annotations require tremendous human effort, limiting the scale a…

cs.CV2025★ 1 cited

Similarity-Guided Layer-Adaptive Vision Transformer for UAV Tracking

Chaocan Xue, Bineng Zhong, Qihua Liang +4

Vision transformers (ViTs) have emerged as a popular backbone for visual tracking. However, complete ViT architectures are too cumbersome to deploy for unmanned aerial vehicle (UAV…

cs.CV2025

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…

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…

cs.CV2024★ 3 cited

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…