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MCDGait: Multimodal Co-Learning Distillation Network with Spatial-Temporal Graph Reasoning for Gait Recognition in the Wild

2024-03-13

Abstract excerpt

<title>Abstract</title> <p>Gait recognition in the wild has attracted the attention of the academic community. However, existing unimodal algorithms cannot achieve the same performance on in-the-wild datasets as in-the-lab datasets because unimodal data have many limitations in-the-wild environments. Therefore, we propose a multimodal approach combining silhouettes and skeletons and formulates the multimodal gait...

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Literature Corpus work: 754c77d6-473a-58d5-b633-874cb39c2aaf
DOI: 10.21203/rs.3.rs-4037908/v1

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MCDGait: Multimodal Co-Learning Distillation Network with Spatial-Temporal Graph Reasoning for Gait Recognition in the WildDOI 10.21203/rs.3.rs-4037908/v1Read

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