Alias-Free Generative Adversarial Networks
We observe that despite their hierarchical convolutional nature, the synthesis process of typical generative adversarial networks depends on absolute pixel coordinates in an unhealthy manner. This manifests itself as, e.g., detail appearing to be glued to image coordinates instead of the surfaces of depicted objects. We trace the root cause to careless signal processing that causes aliasing in the generator network. Interpreting all signals in the network as continuous, we derive generally applicable, small architectural changes that guarantee that unwanted information cannot leak into the hierarchical synthesis process. The resulting networks match the FID of StyleGAN2 but differ dramatically in their internal representations, and they are fully equivariant to translation and rotation even at subpixel scales. Our results pave the way for generative models better suited for video and animation.
PDF Abstract NeurIPS 2021 PDF NeurIPS 2021 AbstractCode
Colab
Tasks
FFHQ
AFHQ
MetFaces
| Task | Dataset | Model | Metric Name | Metric Value | Global Rank | Benchmark |
|---|---|---|---|---|---|---|
| Image Generation | AFHQV2 | Alias-Free-R | FID | 4.40 | # 3 | |
| EQ-T | 64.89 | # 1 | ||||
| EQ-R | 40.34 | # 1 | ||||
| Image Generation | AFHQV2 | Alias-Free-T | FID | 4.04 | # 2 | |
| EQ-T | 60.15 | # 2 | ||||
| EQ-R | 13.51 | # 2 | ||||
| Image Generation | AFHQV2 | StyleGAN2 | FID | 4.62 | # 4 | |
| EQ-T | 13.83 | # 3 | ||||
| EQ-R | 11.50 | # 3 | ||||
| Image Generation | FFHQ 1024 x 1024 | StyleGAN3-R | FID | 3.07 | # 8 | |
| Image Generation | FFHQ 1024 x 1024 | StyleGAN3-T | FID | 2.79 | # 5 | |
| Image Generation | FFHQ-U | StyleGAN2 + Boundaries & upsampling | FID | 6.02 | # 12 | |
| EQ-T | 24.62 | # 8 | ||||
| EQ-R | 10.97 | # 5 | ||||
| Image Generation | FFHQ-U | StyleGAN2 + Simplified generator | FID | 5.21 | # 11 | |
| EQ-T | 19.47 | # 9 | ||||
| EQ-R | 10.41 | # 12 | ||||
| Image Generation | FFHQ-U | StyleGAN2 + No noise inputs | FID | 4.54 | # 5 | |
| EQ-T | 15.81 | # 12 | ||||
| EQ-R | 10.84 | # 6 | ||||
| Image Generation | FFHQ-U | StyleGAN2 | FID | 5.14 | # 10 | |
| Image Generation | FFHQ-U | StyleGAN2 + Transformed Fourier features | FID | 4.64 | # 7 | |
| EQ-T | 45.20 | # 5 | ||||
| EQ-R | 10.61 | # 11 | ||||
| Image Generation | FFHQ-U | StyleGAN2 + Fourier features | FID | 4.79 | # 9 | |
| EQ-T | 16.23 | # 10 | ||||
| EQ-R | 10.81 | # 8 | ||||
| Image Generation | FFHQ-U | Alias-Free-T | FID | 3.67 | # 2 | |
| EQ-T | 61.69 | # 4 | ||||
| EQ-R | 13.95 | # 3 | ||||
| Image Generation | FFHQ-U | StyleGAN2 (70000 img, 1024^2, train from scratch) | FID | 3.79 | # 3 | |
| EQ-T | 15.89 | # 11 | ||||
| EQ-R | 10.79 | # 10 | ||||
| Image Generation | FFHQ-U | Alias-Free-R | FID | 3.66 | # 1 | |
| EQ-T | 64.78 | # 2 | ||||
| EQ-R | 47.64 | # 1 | ||||
| Image Generation | FFHQ-U | StyleGAN2 + Rotation equiv. (Alias-Free-R) | FID | 4.50 | # 4 | |
| EQ-T | 66.65 | # 1 | ||||
| EQ-R | 40.48 | # 2 | ||||
| Image Generation | FFHQ-U | StyleGAN2 + Flexible layers (Alias-Free-T) | FID | 4.62 | # 6 | |
| EQ-T | 63.01 | # 3 | ||||
| EQ-R | 13.12 | # 4 | ||||
| Image Generation | FFHQ-U | StyleGAN2 + Non-critical sampling | FID | 4.78 | # 8 | |
| EQ-T | 43.90 | # 6 | ||||
| EQ-R | 10.84 | # 6 | ||||
| Image Generation | FFHQ-U | StyleGAN2 + Filtered nonlinearities | FID | 6.35 | # 13 | |
| EQ-T | 30.60 | # 7 | ||||
| EQ-R | 10.81 | # 8 | ||||
| Image Generation | MetFaces-U | Alias-Free-R | FID | 18.75 | # 1 | |
| EQ-T | 66.34 | # 1 | ||||
| EQ-R | 48.57 | # 1 | ||||
| Image Generation | MetFaces-U | Alias-Free-T | FID | 18.75 | # 1 | |
| EQ-T | 64.11 | # 2 | ||||
| EQ-R | 16.63 | # 2 | ||||
| Image Generation | MetFaces-U | StyleGAN2 | FID | 18.98 | # 3 | |
| EQ-T | 18.77 | # 3 | ||||
| EQ-R | 13.19 | # 3 |
