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Found 6 papers, 0 papers with code
Action Segmentation Using 2D Skeleton Heatmaps and Multi-Modality Fusion
This paper presents a 2D skeleton-based action segmentation method with applications in fine-grained human activity recognition.
Permutation-Aware Action Segmentation via Unsupervised Frame-to-Segment Alignment
The frame-level prediction module is trained in an unsupervised manner via temporal optimal transport.
Learning by Aligning 2D Skeleton Sequences and Multi-Modality Fusion
This paper presents a self-supervised temporal video alignment framework which is useful for several fine-grained human activity understanding applications.
Timestamp-Supervised Action Segmentation with Graph Convolutional Networks
We introduce a novel approach for temporal activity segmentation with timestamp supervision.
Unsupervised Action Segmentation by Joint Representation Learning and Online Clustering
The temporal optimal transport module enables our approach to learn effective representations for unsupervised activity segmentation.
Learning by Aligning Videos in Time
To overcome this problem, we propose a temporal regularization term (i. e., Contrastive-IDM) which encourages different frames to be mapped to different points in the embedding space.
