Lipreading On Lip Reading In The Wild
Métriques
Top-1 Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Top-1 Accuracy |
|---|---|
| can-we-read-speech-beyond-the-lips-rethinking | 85.02 |
| distinguishing-homophenes-using-multi-head-1 | 88.5 |
| training-strategies-for-improved-lip-reading | 94.1 |
| deformation-flow-based-two-stream-network-for | 84.13 |
| syncvsr-data-efficient-visual-speech | 95.0 |
| audio-visual-speech-recognition-based-on | 89.57 |
| multi-grained-spatio-temporal-modeling-for | 83.34 |
| pseudo-convolutional-policy-gradient-for | 83.5 |
| spotfast-networks-with-memory-augmented | 84.4 |
| lipreading-using-temporal-convolutional | 85.30 |
| visual-speech-recognition-in-a-driver | 88.7 |
| accurate-and-resource-efficient-lipreading | 89.52 |
| combining-residual-networks-with-lstms-for | 83.00 |
| learn-an-effective-lip-reading-model-without | 85.5 |
| leveraging-uni-modal-self-supervised-learning-1 | 85.0 |
| multi-modality-associative-bridging-through-1 | 85.4 |
| towards-practical-lipreading-with-distilled | 88.5 |
| mutual-information-maximization-for-effective | 84.41 |
| end-to-end-audiovisual-speech-recognition | 83.39 |
| learn-an-effective-lip-reading-model-without | 88.4 |
| discriminative-multi-modality-speech | 84.80 |
| syncvsr-data-efficient-visual-speech | 93.2 |