Visual Question Answering On Clevr Humans
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Model Name | Accuracy | Paper Title | Repository |
|---|---|---|---|
| MAC | 81.5 | Compositional Attention Networks for Machine Reasoning | |
| IEP-18K | 66.6 | Inferring and Executing Programs for Visual Reasoning | |
| NS-VQA (1K programs) | 67.8 | Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding | |
| MDETR | 81.7 | MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding | |
| CNN+GRU+FiLM | 75.9 | FiLM: Visual Reasoning with a General Conditioning Layer |
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