SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–125 of 419 papers

TitleStatusHype
B2C-AFM: Bi-Directional Co-Temporal and Cross-Spatial Attention Fusion Model for Human Action RecognitionCode1
Skeleton Aware Multi-modal Sign Language RecognitionCode1
Improving Phenotype Prediction using Long-Range Spatio-Temporal Dynamics of Functional ConnectivityCode1
Spatial Temporal Graph Attention Network for Skeleton-Based Action RecognitionCode1
Skeleton-based Action Recognition via Spatial and Temporal Transformer NetworksCode1
Spatial Temporal Transformer Network for Skeleton-based Action RecognitionCode1
HYperbolic Self-Paced Learning for Self-Supervised Skeleton-based Action RepresentationsCode1
STARS: Self-supervised Tuning for 3D Action Recognition in Skeleton SequencesCode1
Hypergraph Transformer for Skeleton-based Action RecognitionCode1
Subspace Clustering for Action Recognition with Covariance Representations and Temporal PruningCode1
InfoGCN: Representation Learning for Human Skeleton-Based Action RecognitionCode1
Interactive Spatiotemporal Token Attention Network for Skeleton-based General Interactive Action RecognitionCode1
Sign Language Recognition via Skeleton-Aware Multi-Model EnsembleCode1
Topology-aware Convolutional Neural Network for Efficient Skeleton-based Action RecognitionCode1
A Dense-Sparse Complementary Network for Human Action Recognition based on RGB and Skeleton ModalitiesCode1
InfoGCN++: Learning Representation by Predicting the Future for Online Human Skeleton-based Action RecognitionCode1
Understanding the Robustness of Skeleton-based Action Recognition under Adversarial AttackCode1
UNIK: A Unified Framework for Real-world Skeleton-based Action RecognitionCode1
Frequency Guidance Matters: Skeletal Action Recognition by Frequency-Aware Mixed TransformerCode1
BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket SportsCode1
Optimized Skeleton-based Action Recognition via Sparsified Graph Regression—0
Hierarchical Graph Convolutional Skeleton Transformer for Action Recognition—0
Adversarial Attack on Skeleton-based Human Action Recognition—0
Signal-SGN: A Spiking Graph Convolutional Network for Skeletal Action Recognition via Learning Temporal-Frequency Dynamics—0
Unifying Graph Embedding Features with Graph Convolutional Networks for Skeleton-based Action Recognition—0
Show:102550
← PrevPage 5 of 17Next →

No leaderboard results yet.