Pedestrian Attribute Recognition as Label-balanced Multi-label Learning

Autor: Zhou, Yibo, Hu, Hai-Miao, Xiang, Yirong, Zhang, Xiaokang, Wu, Haotian

Rooting in the scarcity of most attributes, realistic pedestrian attribute datasets exhibit unduly skewed data distribution, from which two types of model failures are delivered: (1) label imbalance: model predictions lean greatly towards the side of

Externí odkaz: http://arxiv.org/abs/2405.04858

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