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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

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Showing 251–275 of 419 papers

TitleStatusHype
Pose Refinement Graph Convolutional Network for Skeleton-based Action Recognition—0
PoTion: Pose MoTion Representation for Action Recognition—0
Proving the Potential of Skeleton Based Action Recognition to Automate the Analysis of Manual Processes—0
PYSKL: a toolbox for skeleton-based video understanding—0
PYSKL: Towards Good Practices for Skeleton Action Recognition—0
Recognizing Human Actions as the Evolution of Pose Estimation Maps—0
Recovering Complete Actions for Cross-dataset Skeleton Action Recognition—0
Rolling Rotations for Recognizing Human Actions from 3D Skeletal Data—0
SAR-NAS: Skeleton-based Action Recognition via Neural Architecture Searching—0
What and Where: Modeling Skeletons from Semantic and Spatial Perspectives for Action Recognition—0
SCD-Net: Spatiotemporal Clues Disentanglement Network for Self-supervised Skeleton-based Action Recognition—0
Self-attention based anchor proposal for skeleton-based action recognition—0
Self-Attention Network for Skeleton-based Human Action Recognition—0
Self-Supervised 3D Action Representation Learning with Skeleton Cloud Colorization—0
Self-Supervised 3D Skeleton Action Representation Learning With Motion Consistency and Continuity—0
Semantic-guided Cross-Modal Prompt Learning for Skeleton-based Zero-shot Action Recognition—0
Skeletal quads: Human action recognition using joint quadruples—0
Skeleton-based action analysis for ADHD diagnosis—0
Skeleton-based Action Recognition of People Handling Objects—0
Skeleton-based Action Recognition through Contrasting Two-Stream Spatial-Temporal Networks—0
Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates—0
10,000+ Times Accelerated Robust Subset Selection (ARSS)—0
Skeleton Based Action Recognition using a Stacked Denoising Autoencoder with Constraints of Privileged Information—0
Skeleton-based Action Recognition Using LSTM and CNN—0
Skeleton-Based Action Recognition with Synchronous Local and Non-local Spatio-temporal Learning and Frequency Attention—0
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