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 | QSNGAN | FID | 59.61 | — | Unverified |
| 2 | PeerGAN | FID | 51.37 | — | Unverified |
| 3 | ProbGAN | FID | 46.74 | — | Unverified |
| 4 | DC-VAE | FID | 41.9 | — | Unverified |
| 5 | SN-GAN | FID | 40.1 | — | Unverified |
| 6 | Improving MMD GAN | FID | 37.63 | — | Unverified |
| 7 | Dist-GAN | FID | 36.19 | — | Unverified |
| 8 | aw-SN-GAN | FID | 34.72 | — | Unverified |
| 9 | AutoGAN | FID | 31.01 | — | Unverified |
| 10 | DEGAS | FID | 28.76 | — | Unverified |