5 papers
UETrack: A Unified and Efficient Framework for Single Object Tracking
Ben Kang, Jie Zhao, Xin Chen +5
With growing real-world demands, efficient tracking has received increasing attention. However, most existing methods are limited to RGB inputs and struggle in multi-modal scenario…
Exploiting Lightweight Hierarchical ViT and Dynamic Framework for Efficient Visual Tracking
Ben Kang, Xin Chen, Jie Zhao +3
Transformer-based visual trackers have demonstrated significant advancements due to their powerful modeling capabilities. However, their practicality is limited on resource-constra…
Efficient Motion Prompt Learning for Robust Visual Tracking
Jie Zhao, Xin Chen, Yongsheng Yuan +3
Due to the challenges of processing temporal information, most trackers depend solely on visual discriminability and overlook the unique temporal coherence of video data. In this p…
SUTrack: Towards Simple and Unified Single Object Tracking
Xin Chen, Ben Kang, Wanting Geng +4
In this paper, we propose a simple yet unified single object tracking (SOT) framework, dubbed SUTrack. It consolidates five SOT tasks (RGB-based, RGB-Depth, RGB-Thermal, RGB-Event,…
Exploring Enhanced Contextual Information for Video-Level Object Tracking
Ben Kang, Xin Chen, Simiao Lai +3
Contextual information at the video level has become increasingly crucial for visual object tracking. However, existing methods typically use only a few tokens to convey this infor…