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Self-Supervised Action Representation Learning Based on Asymmetric Skeleton Data Augmentation

Contrastive learning has received increasing attention in the field of skeleton-based action representations in recent years. Most contrastive learning methods use simple augmentation strategies to construct pairs of positive samples. When using such pairs of positive samples to learn action represe...

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Principais autores: Hualing Zhou, Xi Li, Dahong Xu, Hong Liu, Jianping Guo, Yihan Zhang
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2022-11-01
Serier:Sensors
Fag:
action representation
contrastive learning
data augmentation
self-supervised
Online adgang:https://www.mdpi.com/1424-8220/22/22/8989
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