Publications (19)
TracKlinic: Diagnosis of Challenge Factors in Visual Tracking
Heng Fan, Fan Yang, Peng Chu +2
Generic visual tracking is difficult due to many challenge factors (e.g., occlusion, blur, etc.). Each of these factors may cause serious problems for a tracking algorithm, and whe…
FAMNet: Joint Learning of Feature, Affinity and Multi-dimensional Assignment for Online Multiple Object Tracking
Peng Chu, Haibin Ling
Data association-based multiple object tracking (MOT) involves multiple separated modules processed or optimized differently, which results in complex method design and requires no…
LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking
Heng Fan, Liting Lin, Fan Yang +7
In this paper, we present LaSOT, a high-quality benchmark for Large-scale Single Object Tracking. LaSOT consists of 1,400 sequences with more than 3.5M frames in total. Each frame…
Lifelong Unsupervised Domain Adaptive Person Re-identification with Coordinated Anti-forgetting and Adaptation
Zhipeng Huang, Zhizheng Zhang, Cuiling Lan +6
Unsupervised domain adaptive person re-identification (ReID) has been extensively investigated to mitigate the adverse effects of domain gaps. Those works assume the target domain…
Graph Neural Network for Hamiltonian-Based Material Property Prediction
Hexin Bai, Peng Chu, Jeng-Yuan Tsai +4
Development of next-generation electronic devices for applications call for the discovery of quantum materials hosting novel electronic, magnetic, and topological properties. Tradi…
RefineVIS: Video Instance Segmentation with Temporal Attention Refinement
Andre Abrantes, Jiang Wang, Peng Chu +2
We introduce a novel framework called RefineVIS for Video Instance Segmentation (VIS) that achieves good object association between frames and accurate segmentation masks by iterat…