Papers Skeleton Based Action Segmentation
“Skeleton Based Action Segmentation” 태그가 달린 논문 10편 · 필터 해제
Text-Derived Relational Graph-Enhanced Network for Skeleton-Based Action Segmentation
Skeleton-based Temporal Action Segmentation (STAS) aims to segment and recognize various actions from long, untrimmed sequences of human skeletal movements. Current STAS methods typically employ spatio-temporal modeling …
Contrastive LearningSkeleton Based Action SegmentationTAGStitch Contrast and Segment_Learning a Human Action Segmentation Model Using Trimmed Skeleton Videos
Existing skeleton-based human action classification models rely on well-trimmed action-specific skeleton videos for both training and testing, precluding their scalability to real-world applications where untrimmed video…
Action ClassificationAction LocalizationAction SegmentationSegmentation+1Language-Assisted Skeleton Action Understanding for Skeleton-Based Temporal Action Segmentation
Skeleton-based Temporal Action Segmentation (STAS) aims to densely segment and classify human actions in long, untrimmed skeletal motion sequences. Existing STAS methods primarily model spatial dependencies among joints …
Action SegmentationAction UnderstandingContrastive LearningRepresentation Learning+4Language-Assisted Human Part Motion Learning for Skeleton-Based Temporal Action Segmentation
Skeleton-based Temporal Action Segmentation involves the dense action classification of variable-length skeleton sequences. Current approaches primarily apply graph-based networks to extract framewise, whole-body-level m…
Action ClassificationAction SegmentationModel OptimizationRepresentation Learning+2Snippet-Aware Transformer With Multiple Action Elements for Skeleton-Based Action Segmentation
The skeleton-based temporal action segmentation (STAS) aims to densely segment and classify human actions within lengthy untrimmed skeletal motion sequences. Current methods primarily rely on graph convolutional networks…
Action SegmentationSkeleton Based Action SegmentationTemporal Action SegmentationVideo UnderstandingA Decoupled Spatio-Temporal Framework for Skeleton-based Action Segmentation
Effectively modeling discriminative spatio-temporal information is essential for segmenting activities in long action sequences. However, we observe that existing methods are limited in weak spatio-temporal modeling capa…
Action SegmentationSkeleton Based Action SegmentationAction 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. In contrast with state-of-the-art methods which directly take sequences of 3D skeleton coor…
Action SegmentationActivity RecognitionHuman Activity RecognitionSegmentation+1LAC: Latent Action Composition for Skeleton-based Action Segmentation
Skeleton-based action segmentation requires recognizing composable actions in untrimmed videos. Current approaches decouple this problem by first extracting local visual features from skeleton sequences and then processi…
Action SegmentationContrastive LearningSegmentationSkeleton Based Action Segmentation+1LAC - Latent Action Composition for Skeleton-based Action Segmentation
Skeleton-based action segmentation requires recognizing composable actions in untrimmed videos. Current approaches decouple this problem by first extracting local visual features from skeleton sequences and then proc…
Action SegmentationContrastive LearningSegmentationSkeleton Based Action Segmentation+1Skeleton-Based Action Segmentation with Multi-Stage Spatial-Temporal Graph Convolutional Neural Networks
The ability to identify and temporally segment fine-grained actions in motion capture sequences is crucial for applications in human movement analysis. Motion capture is typically performed with optical or inertial measu…
Action SegmentationSkeleton Based Action SegmentationTime SeriesTime Series Analysis