2020

Learning Shape Representations for Clothing Variations in Person Re-Identification

Li, Yu-Jhe, Luo, Zhengyi, Weng, Xinshuo et al.

Understand

Person re-identification (re-ID) aims to recognize instances of the same person contained in multiple images taken across different cameras.

Existing methods for re-ID tend to rely heavily on the assumption that both query and gallery images of the same person have the same clothing.
Unfortunately, this assumption may not hold for datasets captured over long periods of time (e.g., weeks, months or years).
To tackle the re-ID problem in the context of clothing changes, we propose a novel representation learning model which is able to generate a body shape feature representation without being affected by clothing color or patterns.

Built on

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