Image Generation
Image Generation (synthesis) is the task of generating new images from an existing dataset.
- Unconditional generation refers to generating samples unconditionally from the dataset, i.e. $p(y)$
- Conditional image generation (subtask) refers to generating samples conditionally from the dataset, based on a label, i.e. $p(y|x)$.
In this section, you can find state-of-the-art leaderboards for unconditional generation. For conditional generation, and other types of image generations, refer to the subtasks.
( Image credit: StyleGAN )
Papers
Showing 1–10 of 6689 papers
All datasetsImageNet 256x256CIFAR-10ImageNet 64x64ImageNet 512x512FFHQ 256 x 256CelebA 64x64ImageNet 32x32LSUN Bedroom 256 x 256STL-10LSUN Churches 256 x 256ImageNet 128x128FFHQ 1024 x 1024
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SS-GAN (sBN) | FID | 43.87 | — | Unverified |
| 2 | HiT | FID | 30.83 | — | Unverified |
| 3 | PGMGAN | FID | 21.73 | — | Unverified |
| 4 | PR-BigGAN - Precision | FID | 20.76 | — | Unverified |
| 5 | BigGAN-OBRS | FID | 11.65 | — | Unverified |
| 6 | PR-BigGAN - Recall | FID | 9.92 | — | Unverified |
| 7 | BigGAN | FID | 8.7 | — | Unverified |
| 8 | DiffAugment-BigGAN | FID | 6.8 | — | Unverified |
| 9 | CR-BigGAN | FID | 6.66 | — | Unverified |
| 10 | LeCAM + DA | FID | 6.54 | — | Unverified |