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 15511575 of 6689 papers

TitleStatusHype
Exploiting Cultural Biases via Homoglyphs in Text-to-Image SynthesisCode1
One-Shot Synthesis of Images and Segmentation MasksCode1
AI Illustrator: Translating Raw Descriptions into Images by Prompt-based Cross-Modal GenerationCode1
A Scene-Text Synthesis Engine Achieved Through Learning from Decomposed Real-World DataCode1
MMV_Im2Im: An Open Source Microscopy Machine Vision Toolbox for Image-to-Image TransformationCode1
Deep Unrolled Low-Rank Tensor Completion for High Dynamic Range ImagingCode1
Frido: Feature Pyramid Diffusion for Complex Scene Image SynthesisCode1
Training and Tuning Generative Neural Radiance Fields for Attribute-Conditional 3D-Aware Face GenerationCode1
Discovering Transferable Forensic Features for CNN-generated Images DetectionCode1
Improving GANs for Long-Tailed Data through Group Spectral RegularizationCode1
Out-of-distribution Detection via Frequency-regularized Generative ModelsCode1
Paint2Pix: Interactive Painting based Progressive Image Synthesis and EditingCode1
Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion ModelCode1
StyleFaceV: Face Video Generation via Decomposing and Recomposing Pretrained StyleGAN3Code1
High-Frequency Space Diffusion Models for Accelerated MRICode1
Analog Bits: Generating Discrete Data using Diffusion Models with Self-ConditioningCode1
Txt2Img-MHN: Remote Sensing Image Generation from Text Using Modern Hopfield NetworksCode1
Keys to Better Image Inpainting: Structure and Texture Go Hand in HandCode1
Cross Attention Based Style Distribution for Controllable Person Image SynthesisCode1
Generator Knows What Discriminator Should Learn in Unconditional GANsCode1
KUNet: Imaging Knowledge-Inspired Single HDR Image ReconstructionCode1
RealFlow: EM-based Realistic Optical Flow Dataset Generation from VideosCode1
DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific DeltaCode1
Injecting 3D Perception of Controllable NeRF-GAN into StyleGAN for Editable Portrait Image SynthesisCode1
A Survey on Leveraging Pre-trained Generative Adversarial Networks for Image Editing and RestorationCode1
Show:102550
← PrevPage 63 of 268Next →

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