5 papers
CADTrack: Learning Contextual Aggregation with Deformable Alignment for Robust RGBT Tracking
Hao Li, Yuhao Wang, Xiantao Hu +4
RGB-Thermal (RGBT) tracking aims to exploit visible and thermal infrared modalities for robust all-weather object tracking. However, existing RGBT trackers struggle to resolve moda…
Complementary and Contrastive Learning for Audio-Visual Segmentation
Sitong Gong, Yunzhi Zhuge, Lu Zhang +2
Audio-Visual Segmentation (AVS) aims to generate pixel-wise segmentation maps that correlate with the auditory signals of objects. This field has seen significant progress with num…
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…
Two-stream Beats One-stream: Asymmetric Siamese Network for Efficient Visual Tracking
Jiawen Zhu, Huayi Tang, Xin Chen +3
Efficient tracking has garnered attention for its ability to operate on resource-constrained platforms for real-world deployment beyond desktop GPUs. Current efficient trackers mai…
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,…