Browse State-of-the-Art › Clothes Changing Person Re-Identification
Clothes Changing Person Re-Identification
7 papers with code · 0 benchmarks · 0 datasets archive 2025-07-28
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Most implemented papers archive 2025-07-28
7 shown of 7 papers with code (12 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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9 Dec 2023 2 repositories listedPerson Re-Identification (Re-ID) task seeks to enhance the tracking of multiple individuals by surveillance cameras.
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28 Mar 2025 1 repository listedClothes-changing person re-identification (CC-ReID) aims to recognize individuals under different clothing scenarios.
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11 Nov 2024 1 repository listedTo address this issue we propose DLCR, a novel data expansion framework that leverages pre-trained diffusion and large language models (LLMs) to accurately generate diverse images of individuals in varied attire.
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21 Aug 2023 1 repository listedCloth-changing person Re-IDentification (Re-ID) is a particularly challenging task, suffering from two limitations of inferior discriminative features and limited training samples.
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23 May 2023 1 repository listedIn this paper, we address a highly challenging yet critical task: unsupervised long-term person re-identification with clothes change.
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21 Nov 2022 1 repository listedIn this paper, we focus on the relatively new yet practical problem of clothes-changing video-based person re-identification (CCVReID), which is less studied.
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14 Apr 2022 1 repository listed Syntology ran 1 of 1 samples · 0 unverifiedIn this paper, we propose a Clothes-based Adversarial Loss (CAL) to mine clothes-irrelevant features from the original RGB images by penalizing the predictive power of re-id model w.
Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-25.
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