Research map / 3D vision / 3D generation
Binge Watching: Scaling Affordance Learning From Sitcoms
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Increase training data from 2.5K to 25K examples (ablation) | Affordance pose classifier · Friends test set | Top-1 accuracy: 11.7% -> 14.9% | Helped |
| Increase training data from 2.5K to 25K examples (ablation) | Affordance pose classifier · Friends test set | Top-5 accuracy: 41.8% -> 50.9% | Helped |
| Use the two-step pose-classification and VAE approach instead of heatmap regression | Affordance pose prediction · Friends test set | Top-1 accuracy: 8.4 % -> 14.9% | Helped |
| Use the two-step pose-classification and VAE approach instead of heatmap regression | Affordance pose prediction · Friends test set | Top-5 accuracy: 47.3% -> 50.9% | Helped |
| Use heatmap regression instead of the proposed approach | Affordance pose plausibility scoring · Friends scenes with positive and negative poses | Recall at high-recall regimes | Helped |
Closest papers by meaning
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