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 | PresGAN | FID | 52.2 | — | Unverified |
| 2 | RESFLOW | FID | 48.29 | — | Unverified |
| 3 | Residual Flow | FID | 46.37 | — | Unverified |
| 4 | GLF+perceptual loss (ours) | FID | 44.6 | — | Unverified |
| 5 | ProdPoly no activation functions | FID | 40.45 | — | Unverified |
| 6 | ProdPoly no activation functions | FID | 36.77 | — | Unverified |
| 7 | ACGAN | FID | 35.47 | — | Unverified |
| 8 | DenseFlow-74-10 | FID | 34.9 | — | Unverified |
| 9 | NVAE w/ flow | FID | 32.53 | — | Unverified |
| 10 | QSNGAN | FID | 31.97 | — | Unverified |