Identity-Conditioned Score Fusion for Open-Set Person Re-Identification

2026-10-05

AI Summary

This study addresses the fluctuation of model discriminability across identities in open-set person re-identification by proposing a training-free, identity-conditioned score fusion framework. Specifically, this work introduces a parameter-free fusion rule that uniquely integrates both query and gallery identity conditions. By exploiting intra-identity consistency and cross-identity impostor comparisons to extract specific profiles, the framework adaptively customizes fusion weights for each gallery identity. Without requiring additional training, the proposed method significantly enhances the separability between genuine and impostor matches. Extensive experiments demonstrate that it consistently outperforms existing baselines across three clothing-change benchmarks, achieving an absolute reduction of up to 8.8% in the false non-identification rate.

Abstract

Robust person re-identification often combines complementary cues such as face, gait, and body shape. While adaptive fusion typically targets query quality, model strength also varies across identities. We introduce identity-conditioned score fusion, a framework that tailors weights to each gallery identity without training. By contrasting intra-identity consistency against cross-identity impostors, it extracts identity-specific profiles that couple with query-conditioned adaptation via a parameter-free rule. This widens the separation between true and false matches while preserving score calibration. Evaluations on three clothes-changing person re-identification benchmarks show that our method consistently outperforms statistical, rank-based, and learned baselines, achieving up to an 8.8% absolute reduction in the false non-identification rate and demonstrating the value of identity-conditioned fusion in open-set person re-identification.

Problem

• Open-Set Person Re-Identification
• Score Fusion
• Multi-modal Cues
• Identity-Conditioned Adaptation

Innovation

• Identity-Conditioned Score Fusion
• Open-Set Person Re-Identification
• Parameter-Free Rule
• Score Calibration
• Multi-Cue Fusion