May 9, 2024, 4:45 a.m. | Cheng Song, Lu Lu, Zhen Ke, Long Gao, Shuai Ding

cs.CV updates on

arXiv:2405.04900v1 Announce Type: new
Abstract: Emotion recognition is an important part of affective computing. Extracting emotional cues from human gaits yields benefits such as natural interaction, a nonintrusive nature, and remote detection. Recently, the introduction of self-supervised learning techniques offers a practical solution to the issues arising from the scarcity of labeled data in the field of gait-based emotion recognition. However, due to the limited diversity of gaits and the incompleteness of feature representations for skeletons, the existing contrastive learning …

abstract arxiv benefits computing detection emotion human introduction natural nature part practical recognition representation representation learning self-supervised learning solution supervised learning type

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