SCORE: SubDistribution-aware Collaborative Knowledge Reinforcing for Cloth-Hybrid Lifelong Person Re-Identification

Lifelong Person Re-Identification (LReID) aims to train aunified person retrieval model from a non-stationary data stream. Ex-isting LReID methods mainly focus on scenarios where the clothingof each person is consistent. Recently, the Cloth-Hybrid LReID (CH-LReID) where cloth-consistent and cloth-changing data alternately oc-cur, has emerged as a more practical and challenging scenario. Due to theconflict between clothing-relevant and clothing-irrelevant knowledge, thewell-known catastrophic forgetting problem is significantly exacerbatedin this task. To address this issue, we propose a SubDistribution-awareCOllaborative Knowledge REinforcing (SCORE) framework, where ourkey idea is explicitly modeling the intra-identity diversity to continu-ally consolidate distinct cloth-consistent and cloth-changing knowledge.Specifically, an Adaptive SubDistribution Modeling mechanism is devel-oped, where a set of distributional subprototypes is assigned to eachidentity to capture the intra-identity diversity, improving the compati-bility between cloth-consistent and cloth-changing knowledge. Then, aDistributional Knowledge Reinforcement scheme is introduced, wherethe knowledge of old distributional subprototypes is retained in the newones by a collaborative aligning mechanism. Extensive experiments showthat our SCORE achieves the state-of-the-art performance. Our code isavailable at https://github.com/zhoujiahuan1991/ECCV2026-SCORE.