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 | VE (erel=0.01) | FID | 26.46 | — | Unverified |
| 2 | VE (erel=0.02) | FID | 26.46 | — | Unverified |
| 3 | BOSS | clean-FID | 13.21 | — | Unverified |
| 4 | TransGAN | FID | 8.94 | — | Unverified |
| 5 | PNDM | FID | 8.69 | — | Unverified |
| 6 | Denoising Diffusion Probabilistic Model | FID | 7.89 | — | Unverified |
| 7 | PGGAN | FID | 6.42 | — | Unverified |
| 8 | LFM | FID | 5.54 | — | Unverified |
| 9 | DDGAN | FID | 5.25 | — | Unverified |
| 10 | MSG-StyleGAN | FID | 5.2 | — | Unverified |