collaborators

6 papers

cs.CV2026

SAS-VPReID: A Scale-Adaptive Framework with Shape Priors for Video-based Person Re-Identification at Extreme Far Distances

Qiwei Yang, Pingping Zhang, Yuhao Wang +1

Video-based Person Re-IDentification (VPReID) aims to retrieve the same person from videos captured by non-overlapping cameras. At extreme far distances, VPReID is highly challengi…

cs.CV2026

VReID-XFD: Video-based Person Re-identification at Extreme Far Distance Challenge Results

Kailash A. Hambarde, Hugo Proença, Md Rashidunnabi +18

Person re-identification (ReID) across aerial and ground views at extreme far distances introduces a distinct operating regime where severe resolution degradation, extreme viewpoin…

cs.CV2025

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…

cs.CV2025

Signal: Selective Interaction and Global-local Alignment for Multi-Modal Object Re-Identification

Yangyang Liu, Yuhao Wang, Pingping Zhang

Multi-modal object Re-IDentification (ReID) is devoted to retrieving specific objects through the exploitation of complementary multi-modal image information. Existing methods main…

cs.CV2025

AG-VPReID 2025: Aerial-Ground Video-based Person Re-identification Challenge Results

Kien Nguyen, Clinton Fookes, Sridha Sridharan +20

Person re-identification (ReID) across aerial and ground vantage points has become crucial for large-scale surveillance and public safety applications. Although significant progres…

cs.CV2025

IDEA: Inverted Text with Cooperative Deformable Aggregation for Multi-modal Object Re-Identification

Yuhao Wang, Yongfeng Lv, Pingping Zhang +1

Multi-modal object Re-IDentification (ReID) aims to retrieve specific objects by utilizing complementary information from various modalities. However, existing methods focus on fus…