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 | Feature Alignment | FID | 128.35 | — | Unverified |
| 2 | PAE | FID | 49.2 | — | Unverified |
| 3 | FDP(MLP) | FID | 35 | — | Unverified |
| 4 | BEGAN-CS | FID | 34.14 | — | Unverified |
| 5 | PR-BigGAN - Precision | FID | 22.45 | — | Unverified |
| 6 | PeerGAN | FID | 13.95 | — | Unverified |
| 7 | CLR-GAN | FID | 13.63 | — | Unverified |
| 8 | TransGAN-XL | FID | 12.23 | — | Unverified |
| 9 | FCE | FID | 12.21 | — | Unverified |
| 10 | FDP(UViT) | FID | 11 | — | Unverified |