Unsupervised Skeleton Based Action Recognition
5 papers with code • 3 benchmarks • 3 datasets
NTU RGB+D
NTU RGB+D 120
PKU-MMD
Most implemented papers
PREDICT & CLUSTER: Unsupervised Skeleton Based Action Recognition
shlizee/Predict-Cluster
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CVPR 2020
Given inputs of body keypoints sequences obtained during various movements, our system associates the sequences with actions.
Prototypical Contrast and Reverse Prediction: Unsupervised Skeleton Based Action Recognition
Mikexu007/PCRP
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Existing approaches usually learn action representations by sequential prediction but they suffer from the inability to fully learn semantic information.
Unsupervised Motion Representation Learning with Capsule Autoencoders
ZiweiXU/CapsuleMotion
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NeurIPS 2021
We propose the Motion Capsule Autoencoder (MCAE), which addresses a key challenge in the unsupervised learning of motion representations: transformation invariance.
Unsupervised Human Action Recognition with Skeletal Graph Laplacian and Self-Supervised Viewpoints Invariance
iit-pavis/uhar_skeletal_laplacian
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This paper presents a novel end-to-end method for the problem of skeleton-based unsupervised human action recognition.
Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action Recognition
canbaoburen/CoDT
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Furthermore, to leverage the complementarity of domain-shared features and target-specific features, we propose a novel collaborative clustering strategy to enforce pair-wise relationship consistency between the two branches.
