HyperAIHyperAI

Command Palette

Search for a command to run...

Plattform

Skeleton Based Action Recognition On Sbu

Metriken

Accuracy

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Paper Title
Joint Line Distance99.02%On Geometric Features for Skeleton-Based Action Recognition using Multilayer LSTM Networks
MLGCN98.60%MLGCN: Multi-Laplacian Graph Convolutional Networks for Human Action Recognition
VA-fusion (aug.)98.3%View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition
ArmaConv96.00%Graph Neural Networks with convolutional ARMA filters
ChebyNet96.00%Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
DeepGRU95.7%DeepGRU: Deep Gesture Recognition Utility
SGCConv94.0%Simplifying Graph Convolutional Networks
e2eET93.96Real-Time Hand Gesture Recognition: Integrating Skeleton-Based Data Fusion and Multi-Stream CNN
ST-LSTM + Trust Gate93.3%Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition
0 of 9 row(s) selected.
Skeleton Based Action Recognition On Sbu | SOTA | HyperAI