Sign Language Recognition On Autsl
Métriques
Rank-1 Recognition Rate
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Rank-1 Recognition Rate | Paper Title | Repository |
|---|---|---|---|
| FE+LSTM | 0.9338 | Cross-Language Transfer Learning using Visual Information for Automatic Sign Gesture Recognition | - |
| Ensemble - NTIS | 0.9637 | One Model is Not Enough: Ensembles for Isolated Sign Language Recognition | - |
| VTN-PF | 0.9292 | Isolated Sign Recognition from RGB Video using Pose Flow and Self-Attention | |
| 3D-DCNN + ST-MGCN | 0.9842 | Sign Language Recognition via Deformable 3D Convolutions and Modulated Graph Convolutional Networks | - |
| SAM-SLR (RGB-D) | 0.9853 | Skeleton Aware Multi-modal Sign Language Recognition | - |
| MViT-SLR | 0.9572 | Fine-tuning of sign language recognition models: a technical report | - |
| CNN+FPM+BLSTM+Attention (RGB-D) | 0.6203 | AUTSL: A Large Scale Multi-modal Turkish Sign Language Dataset and Baseline Methods | - |
| HWGAT | 0.9580 | Hierarchical Windowed Graph Attention Network and a Large Scale Dataset for Isolated Indian Sign Language Recognition | - |
| STF+LSTM | 0.9856 | Audio-Visual Speech and Gesture Recognition by Sensors of Mobile Devices | - |
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