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CoordGAN: Self-Supervised Dense Correspondences Emerge From GANs
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use CoordGAN correspondence maps for label propagation | dense correspondence evaluation · CelebA-HQ | IoU: 48.50 -> 52.25 | Helped |
| use CoordGAN correspondence maps for label propagation | dense correspondence evaluation · DGAN-face | IoU: 20.36 -> 23.78 | Helped |
| use CoordGAN correspondence maps for label propagation | dense correspondence evaluation · DGAN-car | IoU: 11.07 -> 13.23 | Helped |
| represent structure with a shared coordinate map and vary texture codes | CoordGAN texture swapping · CelebA-HQ, Stanford Cars, AFHQ-cat | LPIPS: 0.58 -> 0.22; 0.61 -> 0.21; 0.55 -> 0.27 | Helped |
| modulate multiple generator layers with the correspondence map (ablation) | CoordGAN · CelebA-HQ | IoU: 48.59 -> 52.25 | Helped |
| add the warp loss (ablation) | CoordGAN generator · CelebA-HQ | IoU: 24.84 -> 52.25 | Helped |
| add the warp loss (ablation) | CoordGAN generator · DGAN-face | IoU: 10.52 -> 23.78 | Helped |
| add the structure swapping constraint (ablation) | CoordGAN generator · CelebA-HQ | IoU: 46.52 -> 52.25 | Helped |
| add the texture swapping constraint (ablation) | CoordGAN generator · CelebA-HQ | IoU: 45.96 -> 52.25 | Helped |
| add a backward MLP with an L1 coordinate supervision loss (ablation) | CoordGAN · CelebA-HQ | IoU: 52.25 -> 54.51 | Helped |
| add a backward MLP with an L1 coordinate supervision loss (ablation) | CoordGAN · DGAN-face | IoU: 23.78 -> 25.44 | Helped |
| add a backward MLP with an L1 coordinate supervision loss (ablation) | CoordGAN · DGAN-car | IoU: 13.23 -> 12.59 | Hurt |
Closest papers by meaning
- GAN-Supervised Dense Visual Alignment (CVPR 2022 · similarity 0.90)
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- A 3D GAN for Improved Large-Pose Facial Recognition (CVPR 2021 · similarity 0.87)
- A Geometric Analysis of Deep Generative Image Models and Its Applications (ICLR 2021 · similarity 0.87)
- MOST-GAN: 3D Morphable StyleGAN for Disentangled Face Image Manipulation (AAAI 2022 · similarity 0.87)
- Learning Dense Correspondence via 3D-Guided Cycle Consistency (CVPR 2016 · similarity 0.86)
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