2024
DOI: 10.1002/cpe.8346
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Enhancing Invariant Feature Learning via Cross‐Composition and Self‐Enrichment Normalization for Visible‐Infrared Person Re‐Identification

Zexin Zhang

Abstract: Visible‐Infrared Person Re‐Identification (VI‐ReID) is a complex challenge in cross‐modality retrieval, wherein the goal is to recognize individuals from images captured via RGB and IR cameras. While many existing methods focus on narrowing the gap between different modalities through designing various feature‐level constraints, they often neglect the consistency of channel statistics information across the modalities, which results in suboptimal matching performance. In this work, we introduce a new approach … Show more

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