Clothes-Changing Person Re-Identification with Feasibility-Aware Intermediary Matching

• URL: http://arxiv.org/abs/2404.09507v1
• Date: Mon, 15 Apr 2024 06:58:09 GMT
• Title: Clothes-Changing Person Re-Identification with Feasibility-Aware Intermediary Matching
• Authors: Jiahe Zhao, Ruibing Hou, Hong Chang, Xinqian Gu, Bingpeng Ma, Shiguang Shan, Xilin Chen,
• Abstract summary: Current clothes-changing person re-identification (re-id) approaches usually perform retrieval based on clothes-irrelevant features. We propose a Feasibility-Aware Intermediary Matching (FAIM) framework to additionally utilize clothes-relevant features for retrieval. Our method outperforms state-of-the-art methods on several widely-used clothes-changing re-id benchmarks.
• Score: 86.04494755636613
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Current clothes-changing person re-identification (re-id) approaches usually perform retrieval based on clothes-irrelevant features, while neglecting the potential of clothes-relevant features. However, we observe that relying solely on clothes-irrelevant features for clothes-changing re-id is limited, since they often lack adequate identity information and suffer from large intra-class variations. On the contrary, clothes-relevant features can be used to discover same-clothes intermediaries that possess informative identity clues. Based on this observation, we propose a Feasibility-Aware Intermediary Matching (FAIM) framework to additionally utilize clothes-relevant features for retrieval. Firstly, an Intermediary Matching (IM) module is designed to perform an intermediary-assisted matching process. This process involves using clothes-relevant features to find informative intermediates, and then using clothes-irrelevant features of these intermediates to complete the matching. Secondly, in order to reduce the negative effect of low-quality intermediaries, an Intermediary-Based Feasibility Weighting (IBFW) module is designed to evaluate the feasibility of intermediary matching process by assessing the quality of intermediaries. Extensive experiments demonstrate that our method outperforms state-of-the-art methods on several widely-used clothes-changing re-id benchmarks.

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