TransNAS-Bench-101
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Semantic Segmentation | TransNAS-Bench-101 Micro level search space | mIoU25.9 | 13 | |
| Surface Normal Prediction | TransNAS-Bench-101 Micro level search space | SSIM58.27 | 13 | |
| Autoencoder | TransNAS-Bench-101 Micro level search space | SSIM56.96 | 13 | |
| Object Classification | TransNAS-Bench-101 Micro level search space | Accuracy45.81 | 13 | |
| Jigsaw | TransNAS-Bench-101 Micro level search space | Accuracy0.9481 | 6 | |
| Semantic Segmentation | TransNAS-Bench-101 Macro Segmentation | Spearman Rho0.83 | 4 | |
| Surface Normal Estimation | TransNAS-Bench-101 Macro (Normal) | Spearman Rho0.85 | 4 | |
| Jigsaw Puzzle Solving | TransNAS-Bench-101 Macro Jigsaw | Spearman Rho0.82 | 4 | |
| Scene Classification | TransNAS-Bench-101 Macro Scene | Spearman Rho0.91 | 4 | |
| Object Classification | TransNAS-Bench-101 Macro (Obj) | Spearman Rho0.92 | 4 | |
| Surface Normal Estimation | TransNAS-Bench-101 Micro Normal | Spearman Rho0.76 | 4 | |
| Jigsaw Puzzle Solving | TransNAS-Bench-101 Micro Jigsaw | Spearman Rho0.6 | 4 | |
| Scene Classification | TransNAS-Bench-101 Micro Scene | Spearman Rho0.79 | 4 | |
| Object Classification | TransNAS-Bench-101 Micro (Obj) | Spearman rho0.61 | 4 | |
| Room Classification | TransNAS-Bench-101 Micro Room | Spearman Rho0.57 | 4 | |
| Autoencoding | TransNAS-Bench-101 Micro AE | Spearman Rho0.45 | 4 |
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