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

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Showing 4901–4950 of 6689 papers

TitleStatusHype
Highly Personalized Text Embedding for Image Manipulation by Stable Diffusion—0
Unsupervised Traffic Scene Generation with Synthetic 3D Scene Graphs—0
Multi-Exposure HDR Composition by Gated Swin Transformer—0
Investigating GANsformer: A Replication Study of a State-of-the-Art Image Generation Model—0
Text-to-image Diffusion Models in Generative AI: A Survey—0
Diffusion Models in NLP: A Survey—0
Interpretable ODE-style Generative Diffusion Model via Force Field Construction—0
SDF-3DGAN: A 3D Object Generative Method Based on Implicit Signed Distance FunctionCode0
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images—0
PARASOL: Parametric Style Control for Diffusion Image Synthesis—0
Regularized Vector Quantization for Tokenized Image Synthesis—0
Self-Supervised One-Shot Learning for Automatic Segmentation of StyleGAN ImagesCode0
Accountable Textual-Visual Chat Learns to Reject Human Instructions in Image Re-creationCode0
Intriguing Property and Counterfactual Explanation of GAN for Remote Sensing Image GenerationCode0
Scaling up GANs for Text-to-Image SynthesisCode0
Learning Stationary Markov Processes with Contrastive AdjustmentCode0
A Prompt Log Analysis of Text-to-Image Generation SystemsCode0
Exploring Efficient-Tuned Learning Audio Representation Method from BriVL—0
M-EBM: Towards Understanding the Manifolds of Energy-Based ModelsCode0
Lformer: Text-to-Image Generation with L-shape Block Parallel Decoding—0
ELODIN: Naming Concepts in Embedding Spaces—0
Neural Style Transfer for Vector GraphicsCode0
LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models—0
Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum Problems—0
How to Construct Energy for Images? Denoising Autoencoder Can Be Energy Based Model—0
Diffusion Models Generate Images Like Painters: an Analytical Theory of Outline First, Details Later—0
Bi-parametric prostate MR image synthesis using pathology and sequence-conditioned stable diffusion—0
X&Fuse: Fusing Visual Information in Text-to-Image Generation—0
Interactive Text Generation—0
StraIT: Non-autoregressive Generation with Stratified Image Transformer—0
Collage Diffusion—0
Can We Use Diffusion Probabilistic Models for 3D Motion Prediction?—0
Semantically Consistent Person Image Generation—0
DEff-GAN: Diverse Attribute Transfer for Few-Shot Image SynthesisCode0
Monocular Depth Estimation using Diffusion Models—0
Differentially Private Diffusion Models Generate Useful Synthetic Images—0
"An Adapt-or-Die Type of Situation": Perception, Adoption, and Use of Text-To-Image-Generation AI by Game Industry Professionals—0
Modulating Pretrained Diffusion Models for Multimodal Image Synthesis—0
Improved Training of Mixture-of-Experts Language GANs—0
Aligning Text-to-Image Models using Human Feedback—0
Controlled and Conditional Text to Image Generation with Diffusion Prior—0
Text Semantics to Image Generation: A method of building facades design base on Stable Diffusion model—0
Gradient Adjusting Networks for Domain InversionCode0
TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts—0
Unpaired Translation from Semantic Label Maps to Images by Leveraging Domain-Specific Simulations—0
Affect-Conditioned Image GenerationCode0
Simple U-net Based Synthetic Polyp Image Generation: Polyp to Negative and Negative to Polyp—0
RePrompt: Automatic Prompt Editing to Refine AI-Generative Art Towards Precise Expressions—0
Redes Generativas Adversarias (GAN) Fundamentos Teóricos y Aplicaciones—0
Combining Generative Artificial Intelligence (AI) and the Internet: Heading towards Evolution or Degradation?—0
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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

#ModelMetricClaimedVerifiedStatus
1Improved DDPMFID12.3—Unverified
2ADMFID11.84—Unverified
3BigGAN-deepFID8.1—Unverified
4Polarity-BigGANFID6.82—Unverified
5VQGAN+Transformer (k=mixed, p=1.0, a=0.005)FID6.59—Unverified
6MaskGITFID6.18—Unverified
7VQGAN+Transformer (k=600, p=1.0, a=0.05)FID5.2—Unverified
8CDMFID4.88—Unverified
9ADM-GFID4.59—Unverified
10RINFID4.51—Unverified
#ModelMetricClaimedVerifiedStatus
1PresGANFID52.2—Unverified
2RESFLOWFID48.29—Unverified
3Residual FlowFID46.37—Unverified
4GLF+perceptual loss (ours)FID44.6—Unverified
5ProdPoly no activation functionsFID40.45—Unverified
6ProdPoly no activation functionsFID36.77—Unverified
7ACGANFID35.47—Unverified
8DenseFlow-74-10FID34.9—Unverified
9NVAE w/ flowFID32.53—Unverified
10QSNGANFID31.97—Unverified
#ModelMetricClaimedVerifiedStatus
1GLIDE + CLSFID30.87—Unverified
2GLIDE + CLIPFID30.46—Unverified
3GLIDE + CLS-FREEFID29.22—Unverified
4GLIDE + CLIP + CLS + CLS-FREEFID29.18—Unverified
5PGMGANFID21.73—Unverified
6CLR-GANFID20.27—Unverified
7FMFID14.45—Unverified
8CT (Direct Generation, NFE=1)FID13—Unverified
9CT (Direct Generation, NFE=2)FID11.1—Unverified
10GLIDE +CLSKID7.95—Unverified