Visual Question Answering On Vizwiz 2020
Métriques
average_precision
f1_score
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | average_precision | f1_score | Paper Title | Repository |
|---|---|---|---|---|
| VT-Transformer (MUL) | 76.96 | 67.26 | - | - |
| VWTest1 | 26.84 | 42.32 | - | - |
| CLIP-Ensemble | 84.13 | - | Less Is More: Linear Layers on CLIP Features as Powerful VizWiz Model | - |
| VT-Transformer (CAT) | 74.91 | 66.7 | - | - |
| BERT-RG-Regression | 52.22 | 41.85 | - | - |
| CLIP-Single | 82.86 | - | Less Is More: Linear Layers on CLIP Features as Powerful VizWiz Model | - |
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