2 citations · 3 across the 12 of their papers we have counts for
12 papers
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…
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…
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…
Difference Feedback: Generating Multimodal Process-Level Supervision for VLM Reinforcement Learning
Feiding, Yongkang Zhang, Yuhao Liao +10
Vision--language models (VLMs) are increasingly aligned via Group Relative Policy Optimization (GRPO)-style training. However, relying solely on terminal outcome rewards yields spa…
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…
Robust RGB-T Tracking via Learnable Visual Fourier Prompt Fine-tuning and Modality Fusion Prompt Generation
Hongtao Yang, Bineng Zhong, Qihua Liang +3
Recently, visual prompt tuning is introduced to RGB-Thermal (RGB-T) tracking as a parameter-efficient finetuning (PEFT) method. However, these PEFT-based RGB-T tracking methods typ…
Towards Universal Modal Tracking with Online Dense Temporal Token Learning
Yaozong Zheng, Bineng Zhong, Qihua Liang +4
We propose a universal video-level modality-awareness tracking model with online dense temporal token learning (called {\modaltracker}). It is designed to support various tracking…
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…
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…
Personalized federated learning based on feature fusion
Wolong Xing, Zhenkui Shi, Hongyan Peng +2
Federated learning enables distributed clients to collaborate on training while storing their data locally to protect client privacy. However, due to the heterogeneity of data, mod…
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…
Towards Unified Token Learning for Vision-Language Tracking
Yaozong Zheng, Bineng Zhong, Qihua Liang +3
In this paper, we present a simple, flexible and effective vision-language (VL) tracking pipeline, termed \textbf{MMTrack}, which casts VL tracking as a token generation task. Trad…