3D Action Recognition
32 papers with code • 2 benchmarks • 13 datasets
Image: Rahmani et al
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CrossGLG: LLM Guides One-shot Skeleton-based 3D Action Recognition in a Cross-level Manner
Most existing one-shot skeleton-based action recognition focuses on raw low-level information (e. g., joint location), and may suffer from local information loss and low generalization ability.
Learning Scene Flow With Skeleton Guidance For 3D Action Recognition
Among the existing modalities for 3D action recognition, 3D flow has been poorly examined, although conveying rich motion information cues for human actions.
Self-Supervised 3D Action Representation Learning with Skeleton Cloud Colorization
We investigate self-supervised representation learning and design a novel skeleton cloud colorization technique that is capable of learning spatial and temporal skeleton representations from unlabeled skeleton sequence data.
Spatial-Temporal Transformer for 3D Point Cloud Sequences
We test the effectiveness our PST2 with two different tasks on point cloud sequences, i. e., 4D semantic segmentation and 3D action recognition.
Unsupervised View-Invariant Human Posture Representation
Most recent view-invariant action recognition and performance assessment approaches rely on a large amount of annotated 3D skeleton data to extract view-invariant features.
Skeleton Cloud Colorization for Unsupervised 3D Action Representation Learning
We investigate unsupervised representation learning for skeleton action recognition, and design a novel skeleton cloud colorization technique that is capable of learning skeleton representations from unlabeled skeleton sequence data.
Real-time Human Action Recognition Using Locally Aggregated Kinematic-Guided Skeletonlet and Supervised Hashing-by-Analysis Model
To tackle all these problems, we propose a real-time 3D action recognition framework by integrating the locally aggregated kinematic-guided skeletonlet (LAKS) with a supervised hashing-by-analysis (SHA) model.
Independent Sign Language Recognition with 3D Body, Hands, and Face Reconstruction
Independent Sign Language Recognition is a complex visual recognition problem that combines several challenging tasks of Computer Vision due to the necessity to exploit and fuse information from hand gestures, body features and facial expressions.
VI-Net: View-Invariant Quality of Human Movement Assessment
We propose a view-invariant method towards the assessment of the quality of human movements which does not rely on skeleton data.
Adversarial Self-Supervised Learning for Semi-Supervised 3D Action Recognition
Self-supervised learning (SSL) has been proved very effective at learning representations from unlabeled data in the image domain.