Lilang Lin

Orcid: 0000-0002-3229-4096

According to our database1, Lilang Lin authored at least 18 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
Self-Supervised Skeleton Representation Learning Via Actionlet Contrast and Reconstruct.
IEEE Trans. Pattern Anal. Mach. Intell., November, 2025

2024
Mutual Information Driven Equivariant Contrastive Learning for 3D Action Representation Learning.
IEEE Trans. Image Process., 2024

S⁵Mars: Semi-Supervised Learning for Mars Semantic Segmentation.
IEEE Trans. Geosci. Remote. Sens., 2024

Coding for Intelligence from the Perspective of Category.
CoRR, 2024

Self-Supervised Skeleton Action Representation Learning: A Benchmark and Beyond.
CoRR, 2024

Shap-Mix: Shapley Value Guided Mixing for Long-Tailed Skeleton Based Action Recognition.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

MacDiff: Unified Skeleton Modeling with Masked Conditional Diffusion.
Proceedings of the Computer Vision - ECCV 2024, 2024

Idempotent Unsupervised Representation Learning for Skeleton-Based Action Recognition.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
Semi-supervised Learning for Mars Imagery Classification and Segmentation.
ACM Trans. Multim. Comput. Commun. Appl., 2023

Prompted Contrast with Masked Motion Modeling: Towards Versatile 3D Action Representation Learning.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

Bayesian Contrastive Learning with Manifold Regularization for Self-Supervised Skeleton Based Action Recognition.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2023

Actionlet-Dependent Contrastive Learning for Unsupervised Skeleton-Based Action Recognition.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Hierarchical Consistent Contrastive Learning for Skeleton-Based Action Recognition with Growing Augmentations.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Learning to Recognize Human Actions From Noisy Skeleton Data Via Noise Adaptation.
IEEE Trans. Multim., 2022

S<sup>5</sup>Mars: Self-Supervised and Semi-Supervised Learning for Mars Segmentation.
CoRR, 2022

2021
Semi-Supervised Learning for Mars Imagery Classification.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

2020
MS<sup>2</sup>L: Multi-Task Self-Supervised Learning for Skeleton Based Action Recognition.
CoRR, 2020

MS2L: Multi-Task Self-Supervised Learning for Skeleton Based Action Recognition.
Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020


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