5 papers
Dual-Edged Homogeneous-Modality Similarity: Towards Visible-Infrared Modality-Incomplete Person Re-Identification with Modality Adaptive Matching
Xin Xu, Shuhao Zhan, Wei Liu +3
Visible-Infrared Person Re-Identification (VI-ReID) operates under a closed-world assumption, where queries and galleries are from heterogeneous modalities. However, in open-world…
Mining Multi-Modality Spatio-Temporal Cues for Video Important Person Identification
Xiao Wang, Minglei Yang, Bin Yang +4
Identifying key individuals in video scenes is essential for applications such as automated video editing and intelligent surveillance. Current methods primarily focus on static im…
From Calibration to Refinement: Seeking Certainty via Probabilistic Evidence Propagation for Noisy-Label Person Re-Identification
Xin Yuan, Zhiyong Zhang, Xin Xu +2
With the increasing demand for robust person Re-ID in unconstrained environments, learning from datasets with noisy labels and sparse per-identity samples remains a critical challe…
Beyond Seen Bounds: Class-Centric Polarization for Single-Domain Generalized Deep Metric Learning
Xin Yuan, Meiqi Wan, Wei Liu +2
Single-domain generalized deep metric learning (SDG-DML) faces the dual challenge of both category and domain shifts during testing, limiting real-world applications. Therefore, ai…
Mix-Modality Person Re-Identification: A New and Practical Paradigm
Wei Liu, Xin Xu, Hua Chang +2
Current visible-infrared cross-modality person re-identification research has only focused on exploring the bi-modality mutual retrieval paradigm, and we propose a new and more pra…