5 papers
Self-Supervised Skeleton-Based Action Representation Learning: A Benchmark and Beyond
Jiahang Zhang, Lilang Lin, Shuai Yang +1
Self-supervised learning (SSL), which aims to learn meaningful prior representations from unlabeled data, has been proven effective for skeleton-based action understanding. Differe…
Idempotent Unsupervised Representation Learning for Skeleton-Based Action Recognition
Lilang Lin, Lehong Wu, Jiahang Zhang +1
Generative models, as a powerful technique for generation, also gradually become a critical tool for recognition tasks. However, in skeleton-based action recognition, the features…
MacDiff: Unified Skeleton Modeling with Masked Conditional Diffusion
Lehong Wu, Lilang Lin, Jiahang Zhang +2
Self-supervised learning has proved effective for skeleton-based human action understanding. However, previous works either rely on contrastive learning that suffers false negative…
Shap-Mix: Shapley Value Guided Mixing for Long-Tailed Skeleton Based Action Recognition
Jiahang Zhang, Lilang Lin, Jiaying Liu
In real-world scenarios, human actions often fall into a long-tailed distribution. It makes the existing skeleton-based action recognition works, which are mostly designed based on…
Coding for Intelligence from the Perspective of Category
Wenhan Yang, Zixuan Hu, Lilang Lin +2
Coding, which targets compressing and reconstructing data, and intelligence, often regarded at an abstract computational level as being centered around model learning and predictio…