Visual Question Answering On Clevr Humans
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy |
|---|---|
| compositional-attention-networks-for-machine | 81.5 |
| inferring-and-executing-programs-for-visual | 66.6 |
| neural-symbolic-vqa-disentangling-reasoning | 67.8 |
| mdetr-modulated-detection-for-end-to-end | 81.7 |
| film-visual-reasoning-with-a-general | 75.9 |