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Skeleton Based Action Recognition

Skeleton-based Action Recognition is a computer vision task that involves recognizing human actions from a sequence of 3D skeletal joint data captured from sensors such as Microsoft Kinect, Intel RealSense, and wearable devices. The goal of skeleton-based action recognition is to develop algorithms that can understand and classify human actions from skeleton data, which can be used in various applications such as human-computer interaction, sports analysis, and surveillance.

( Image credit: View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition )

Papers

Showing 76100 of 419 papers

TitleStatusHype
Navigating Open Set Scenarios for Skeleton-based Action RecognitionCode1
STEP CATFormer: Spatial-Temporal Effective Body-Part Cross Attention Transformer for Skeleton-based Action RecognitionCode0
Hulk: A Universal Knowledge Translator for Human-Centric TasksCode2
VSViG: Real-time Video-based Seizure Detection via Skeleton-based Spatiotemporal ViGCode1
Challenges in Video-Based Infant Action Recognition: A Critical Examination of the State of the ArtCode1
SkelVIT: Consensus of Vision Transformers for a Lightweight Skeleton-Based Action Recognition System0
InfoGCN++: Learning Representation by Predicting the Future for Online Human Skeleton-based Action RecognitionCode1
Proving the Potential of Skeleton Based Action Recognition to Automate the Analysis of Manual Processes0
Elevating Skeleton-Based Action Recognition with Efficient Multi-Modality Self-SupervisionCode0
Exploring Self-supervised Skeleton-based Action Recognition in Occluded EnvironmentsCode1
SkeleTR: Towrads Skeleton-based Action Recognition in the Wild0
Multi-Semantic Fusion Model for Generalized Zero-Shot Skeleton-Based Action RecognitionCode1
SCD-Net: Spatiotemporal Clues Disentanglement Network for Self-supervised Skeleton-based Action Recognition0
B2C-AFM: Bi-Directional Co-Temporal and Cross-Spatial Attention Fusion Model for Human Action RecognitionCode1
SiT-MLP: A Simple MLP with Point-wise Topology Feature Learning for Skeleton-based Action RecognitionCode1
Balanced Representation Learning for Long-tailed Skeleton-based Action RecognitionCode0
Local Spherical Harmonics Improve Skeleton-Based Hand Action RecognitionCode0
Ske2Grid: Skeleton-to-Grid Representation Learning for Action RecognitionCode1
Masked Motion Predictors are Strong 3D Action Representation LearnersCode1
Zero-shot Skeleton-based Action Recognition via Mutual Information Estimation and MaximizationCode1
SkeletonMAE: Graph-based Masked Autoencoder for Skeleton Sequence Pre-trainingCode1
Cross-Model Cross-Stream Learning for Self-Supervised Human Action RecognitionCode0
Interactive Spatiotemporal Token Attention Network for Skeleton-based General Interactive Action RecognitionCode1
Miniaturized Graph Convolutional Networks with Topologically Consistent Pruning0
Multi-Dimensional Refinement Graph Convolutional Network with Robust Decouple Loss for Fine-Grained Skeleton-Based Action Recognition0
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