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 26512675 of 6689 papers

TitleStatusHype
Bridging Generative and Discriminative Models for Unified Visual Perception with Diffusion Priors0
DiffMoE: Dynamic Token Selection for Scalable Diffusion Transformers0
A Novel Framework for Image-to-image Translation and Image Compression0
Diff-MM: Exploring Pre-trained Text-to-Image Generation Model for Unified Multi-modal Object Tracking0
DiffLoRA: Generating Personalized Low-Rank Adaptation Weights with Diffusion0
Bridging CLIP and StyleGAN through Latent Alignment for Image Editing0
A novel deep learning-based method for monochromatic image synthesis from spectral CT using photon-counting detectors0
DiffI2I: Efficient Diffusion Model for Image-to-Image Translation0
BRIDGING ADVERSARIAL SAMPLES AND ADVERSARIAL NETWORKS0
DiffGAR: Model-Agnostic Restoration from Generative Artifacts Using Image-to-Image Diffusion Models0
Bridge Diffusion Model: bridge non-English language-native text-to-image diffusion model with English communities0
DiffGAN: A Test Generation Approach for Differential Testing of Deep Neural Networks0
Differentially Private Fine-Tuning of Diffusion Models0
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images0
Advancing Generative Model Evaluation: A Novel Algorithm for Realistic Image Synthesis and Comparison in OCR System0
High-Resolution Image Synthesis via Next-Token Prediction0
High Resolution Solar Image Generation using Generative Adversarial Networks0
Differentially Private Diffusion Models Generate Useful Synthetic Images0
BraSyn 2023 challenge: Missing MRI synthesis and the effect of different learning objectives0
An Ordinary Differential Equation Sampler with Stochastic Start for Diffusion Bridge Models0
Advancing Diffusion Models: Alias-Free Resampling and Enhanced Rotational Equivariance0
4D Semantic Cardiac Magnetic Resonance Image Synthesis on XCAT Anatomical Model0
BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity0
Brain Image Synthesis With Unsupervised Multivariate Canonical CSCl4Net0
An Ordinal Diffusion Model for Generating Medical Images with Different Severity Levels0
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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