Unsupervised Skeleton Based Action Recognition

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

7 shown of 7 papers with code (11 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Attack-Augmentation Mixing-Contrastive Skeletal Representation Learning
  8 Apr 2023 1 repository listed
  In particular, we propose a novel Attack-Augmentation Mixing-Contrastive skeletal representation learning (A²MC) to contrast hard positive features and hard negative features for learning more robust skeleton…
• HYperbolic Self-Paced Learning for Self-Supervised Skeleton-based Action Representations
  10 Mar 2023 1 repository listed Syntology ran 2 of 13 samples · 11 unverified
  We propose to use hyperbolic uncertainty to determine the algorithmic learning pace, under the assumption that less uncertain samples should be more strongly driving the training, with a larger weight and pace.
• Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action Recognition
  20 Jul 2022 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  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…
• Unsupervised Human Action Recognition with Skeletal Graph Laplacian and Self-Supervised Viewpoints Invariance
  21 Apr 2022 1 repository listed
  This paper presents a novel end-to-end method for the problem of skeleton-based unsupervised human action recognition.
• Unsupervised Motion Representation Learning with Capsule Autoencoders
  1 Oct 2021 1 repository listed Syntology ran 15 of 20 samples · 5 unverified
  We propose the Motion Capsule Autoencoder (MCAE), which addresses a key challenge in the unsupervised learning of motion representations: transformation invariance.
• Prototypical Contrast and Reverse Prediction: Unsupervised Skeleton Based Action Recognition
  14 Nov 2020 1 repository listed
  Existing approaches usually learn action representations by sequential prediction but they suffer from the inability to fully learn semantic information.
• PREDICT & CLUSTER: Unsupervised Skeleton Based Action Recognition
  27 Nov 2019 1 repository listed
  Given inputs of body keypoints sequences obtained during various movements, our system associates the sequences with actions.

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.