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New network tackles visible-infrared person re-identification challenges

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a Multi-Frequency Expert Network (MFEN) to address the challenges in visible-infrared person re-identification (VI-ReID). The network aims to overcome the significant modality discrepancy between visible and infrared images, which is often caused by differing lighting conditions. MFEN utilizes a mixture-of-experts design to adaptively combine information from various frequency bands, enhancing the extraction of identity-relevant details while filtering out lighting variations. The approach is further supported by Random Frequency Augmentation and Frequency Auxiliary Optimization techniques to improve training and robust representation learning. AI

IMPACT Introduces a novel approach to improve person re-identification across different visual spectra, potentially enhancing surveillance and security systems.

RANK_REASON The cluster contains an academic paper detailing a new method for a computer vision task.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New network tackles visible-infrared person re-identification challenges

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The cluster contains an academic paper detailing a new method for a computer vision task.
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COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Xulin Li, Yan Lu, Bin Liu, Qinhong Yang, Qi Chu, Tao Gong, Nenghai Yu ·

    MFEN:Multi-Frequency Expert Network for Visible-Infrared Person Re-ID

    arXiv:2606.12051v1 Announce Type: new Abstract: Visible-infrared person re-identification (VI-ReID) is challenging due to the large modality discrepancy between visible and infrared images. We contend that this discrepancy is largely related to differing lighting conditions, incl…

  2. arXiv cs.CV TIER_1 English(EN) · Nenghai Yu ·

    MFEN:Multi-Frequency Expert Network for Visible-Infrared Person Re-ID

    Visible-infrared person re-identification (VI-ReID) is challenging due to the large modality discrepancy between visible and infrared images. We contend that this discrepancy is largely related to differing lighting conditions, including differences in light wavelength and light …

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