FlexiReID: Adaptive Mixture of Expert for Multi-Modal Person Re-Identification

• URL: http://arxiv.org/abs/2510.15595v1
• Date: Fri, 17 Oct 2025 12:41:05 GMT
• Title: FlexiReID: Adaptive Mixture of Expert for Multi-Modal Person Re-Identification
• Authors: Zhen Sun, Lei Tan, Yunhang Shen, Chengmao Cai, Xing Sun, Pingyang Dai, Liujuan Cao, Rongrong Ji,
• Abstract summary: FlexiReID is a flexible framework that supports seven retrieval modes across four modalities.<n>We construct CIRS-PEDES, a unified dataset extending four popular Re-ID datasets to include all four modalities.
• Score: 88.61193805417024
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Multimodal person re-identification (Re-ID) aims to match pedestrian images across different modalities. However, most existing methods focus on limited cross-modal settings and fail to support arbitrary query-retrieval combinations, hindering practical deployment. We propose FlexiReID, a flexible framework that supports seven retrieval modes across four modalities: rgb, infrared, sketches, and text. FlexiReID introduces an adaptive mixture-of-experts (MoE) mechanism to dynamically integrate diverse modality features and a cross-modal query fusion module to enhance multimodal feature extraction. To facilitate comprehensive evaluation, we construct CIRS-PEDES, a unified dataset extending four popular Re-ID datasets to include all four modalities. Extensive experiments demonstrate that FlexiReID achieves state-of-the-art performance and offers strong generalization in complex scenarios.

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