SOTAVerified

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 59515975 of 6689 papers

TitleStatusHype
Diversifying Semantic Image Synthesis and Editing via Class- and Layer-wise VAEsCode0
Pixel-wise Conditioning of Generative Adversarial NetworksCode0
Instance Normalization: The Missing Ingredient for Fast StylizationCode0
CSGAN: Cyclic-Synthesized Generative Adversarial Networks for Image-to-Image TransformationCode0
MoEdit: On Learning Quantity Perception for Multi-object Image EditingCode0
Few-shot Image Generation via Masked DiscriminationCode0
Synthetic Lung Nodule 3D Image Generation Using AutoencodersCode0
Few-shot Image Generation with Diffusion ModelsCode0
PKU-AIGIQA-4K: A Perceptual Quality Assessment Database for Both Text-to-Image and Image-to-Image AI-Generated ImagesCode0
Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative ModelsCode0
URCDM: Ultra-Resolution Image Synthesis in HistopathologyCode0
Dual Projection Generative Adversarial Networks for Conditional Image GenerationCode0
XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities GenerationCode0
Instant Photorealistic Neural Radiance Fields StylizationCode0
Diversity in deep generative models and generative AICode0
FHDR: HDR Image Reconstruction from a Single LDR Image using Feedback NetworkCode0
A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning ConventionsCode0
Towards Equitable Representation in Text-to-Image Synthesis Models with the Cross-Cultural Understanding Benchmark (CCUB) DatasetCode0
FIGR: Few-shot Image Generation with ReptileCode0
SITA: Structurally Imperceptible and Transferable Adversarial Attacks for Stylized Image GenerationCode0
Carton dataset synthesis method for domain shift based on foreground texture decoupling and replacementCode0
Block Flow: Learning Straight Flow on Data BlocksCode0
Skeleton-Guided Diffusion Model for Accurate Foot X-ray Synthesis in Hallux Valgus DiagnosisCode0
Finding Local Diffusion Schrödinger Bridge using Kolmogorov-Arnold NetworkCode0
Finding Local Diffusion Schrodinger Bridge using Kolmogorov-Arnold NetworkCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Improved DDPMFID12.3Unverified
2ADMFID11.84Unverified
3BigGAN-deepFID8.1Unverified
4Polarity-BigGANFID6.82Unverified
5VQGAN+Transformer (k=mixed, p=1.0, a=0.005)FID6.59Unverified
6MaskGITFID6.18Unverified
7VQGAN+Transformer (k=600, p=1.0, a=0.05)FID5.2Unverified
8CDMFID4.88Unverified
9ADM-GFID4.59Unverified
10RINFID4.51Unverified
#ModelMetricClaimedVerifiedStatus
1PresGANFID52.2Unverified
2RESFLOWFID48.29Unverified
3Residual FlowFID46.37Unverified
4GLF+perceptual loss (ours)FID44.6Unverified
5ProdPoly no activation functionsFID40.45Unverified
6ProdPoly no activation functionsFID36.77Unverified
7ACGANFID35.47Unverified
8DenseFlow-74-10FID34.9Unverified
9NVAE w/ flowFID32.53Unverified
10QSNGANFID31.97Unverified
#ModelMetricClaimedVerifiedStatus
1GLIDE + CLSFID30.87Unverified
2GLIDE + CLIPFID30.46Unverified
3GLIDE + CLS-FREEFID29.22Unverified
4GLIDE + CLIP + CLS + CLS-FREEFID29.18Unverified
5PGMGANFID21.73Unverified
6CLR-GANFID20.27Unverified
7FMFID14.45Unverified
8CT (Direct Generation, NFE=1)FID13Unverified
9CT (Direct Generation, NFE=2)FID11.1Unverified
10GLIDE +CLSKID7.95Unverified