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 | QC-NCSN++ | FID | 19.62 | — | Unverified |
| 2 | NDM | FID | 17.02 | — | Unverified |
| 3 | DDPM | FID | 16.18 | — | Unverified |
| 4 | MSGAN | FID | 12.3 | — | Unverified |
| 5 | i-DODE | FID | 9.09 | — | Unverified |
| 6 | DDPM++ (VP, NLL) + ST | FID | 8.42 | — | Unverified |
| 7 | MDM | FID | 7.91 | — | Unverified |
| 8 | MDM-Prime | FID | 6.98 | — | Unverified |
| 9 | FM | FID | 5.02 | — | Unverified |
| 10 | Real NVP (Dinh et al., 2017) | bpd | 4.28 | — | Unverified |