27 citations · 70 across the 9 of their papers we have counts for
11 papers · 1 filter
TransMOT: Spatial-Temporal Graph Transformer for Multiple Object Tracking
Peng Chu, Jiang Wang, Quanzeng You +2
Tracking multiple objects in videos relies on modeling the spatial-temporal interactions of the objects. In this paper, we propose a solution named TransMOT, which leverages powerf…
GMOT-40: A Benchmark for Generic Multiple Object Tracking
Hexin Bai, Wensheng Cheng, Peng Chu +3
Multiple Object Tracking (MOT) has witnessed remarkable advances in recent years. However, existing studies dominantly request prior knowledge of the tracking target, and hence may…
LaSOT: A High-quality Large-scale Single Object Tracking Benchmark
Heng Fan, Hexin Bai, Liting Lin +11
Despite great recent advances in visual tracking, its further development, including both algorithm design and evaluation, is limited due to lack of dedicated large-scale benchmark…
Feature Space Augmentation for Long-Tailed Data
Peng Chu, Xiao Bian, Shaopeng Liu +1
Real-world data often follow a long-tailed distribution as the frequency of each class is typically different. For example, a dataset can have a large number of under-represented c…
Map3D: Registration Based Multi-Object Tracking on 3D Serial Whole Slide Images
Ruining Deng, Haichun Yang, Aadarsh Jha +4
There has been a long pursuit for precise and reproducible glomerular quantification on renal pathology to leverage both research and practice. When digitizing the biopsy tissue sa…
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…