Clothes-Changing Person Re-Identification with Feasibility-Aware
  Intermediary Matching
Jiahe Zhao Ruibing Hou Hong Chang Xinqian Gu Bingpeng Ma Shiguang Shan Xilin Chen
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.