Bedroom
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Secret information extraction | Bedroom | Accuracy99.99 | 29 | |
| 3D Indoor Scene Synthesis | Bedroom (Standard Split) | CNR45.9 | 13 | |
| Semantic Segmentation | Bedroom dataset | Bed Accuracy89.47 | 7 | |
| Inpainting | Bedroom | PSNR28.883 | 6 | |
| Nonlinear deblurring | Bedroom | PSNR22.67 | 6 | |
| Gaussian deblurring | Bedroom | PSNR25.28 | 6 | |
| Anti-steganalysis | Bedroom | YeNet Score0.9901 | 5 | |
| Semantic Image Generation | Bedroom StyleGAN2 (test) | Semantic Accuracy22.3 | 5 | |
| Image Colorization | Bedroom (test) | AuC90.02 | 5 | |
| Super-Resolution | Bedroom | PSNR26.59 | 4 | |
| Physical Plausibility Assessment | Bedroom | Total Intersection Volume241.25 | 4 | |
| 3D indoor scene synthesis from natural language | Bedroom | iRecall70.45 | 4 | |
| Unconditioned Indoor Scene Generation | Bedroom (test) | FID123.42 | 4 | |
| Indoor Scene Stylization | Bedroom (test) | Delta (1e-3)7.03 | 4 | |
| Indoor Scene Completion | Bedroom (test) | FID81.83 | 4 | |
| Indoor Scene Re-arrangement | Bedroom (test) | FID105.71 | 3 | |
| 4x Super-resolution | Bedroom | PSNR26.587 | 2 | |
| Label-scarce Semantic Segmentation | Bedroom-28 | Metric- | 0 |
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