AI RESEARCH

Thinking Before Matching: A Reinforcement Reasoning Paradigm Towards General Person Re-Identification

arXiv CS.CV

ArXi:2604.19218v1 Announce Type: new Learning identity-discriminative representations with multi-scene generality has become a critical objective in person re-identification (ReID). However, mainstream perception-driven paradigms tend to identify fitting from massive annotated data rather than identity-causal cues understanding, which presents a fragile representation against multiple disruptions. In this work, ReID-R is proposed as a novel reasoning-driven paradigm that achieves explicit identity understanding and reasoning by incorporating chain-of-thought into the ReID pipeline.