Summary of Disentangled Representations For Short-term and Long-term Person Re-identification, by Chanho Eom et al.
Disentangled Representations for Short-Term and Long-Term Person Re-Identification
by Chanho Eom, Wonkyung Lee, Geon Lee, Bumsub Ham
First submitted to arxiv on: 9 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary In this paper, researchers tackle the problem of person re-identification (reID), which involves retrieving person images from a large dataset given a query image. The key challenge is learning robust person representations that can account for intra-class variations. Recent methods focus on learning features discriminative for specific factors of variations, requiring corresponding annotations. To address this issue, the authors propose factoring person images into identity-related and unrelated features using an identity shuffle GAN (IS-GAN). IS-GAN disentangles these features through an identity-shuffling technique that relies only on identification labels without auxiliary supervisory signals. Experimental results show state-of-the-art performance on standard reID benchmarks, including Market-1501, CUHK03, and DukeMTMC-reID. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us better recognize people in photos or videos by developing a new way to understand what makes each person unique. The authors create a machine learning model called IS-GAN that separates a person’s identity from other features like their pose or clothes. This allows the model to learn more about who someone is, even if they’re seen from different angles or wearing different outfits. The results show that this new approach works better than previous methods on several important benchmarks. |
Keywords
» Artificial intelligence » Gan » Machine learning
