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 21762200 of 6689 papers

TitleStatusHype
Generalized Compressed Sensing for Image Reconstruction with Diffusion Probabilistic ModelsCode0
CLR-GAN: Improving GANs Stability and Quality via Consistent Latent Representation and ReconstructionCode0
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality TransferCode0
Artificial Generation of Big Data for Improving Image Classification: A Generative Adversarial Network Approach on SAR DataCode0
Optimal Eye Surgeon: Finding Image Priors through Sparse Generators at InitializationCode0
Optimal Linear Subspace Search: Learning to Construct Fast and High-Quality Schedulers for Diffusion ModelsCode0
Padding Tone: A Mechanistic Analysis of Padding Tokens in T2I ModelsCode0
ClothFlow: A Flow-Based Model for Clothed Person GenerationCode0
Open-Source Acceleration of Stable-Diffusion.cpp Deployable on All DevicesCode0
Adversarial Synthesis Learning Enables Segmentation Without Target Modality Ground TruthCode0
ArtGAN: Artwork Synthesis with Conditional Categorical GANsCode0
On the Issues of TrueDepth Sensor Data for Computer Vision Tasks Across Different iPad GenerationsCode0
DRMC: A Generalist Model with Dynamic Routing for Multi-Center PET Image SynthesisCode0
The Art of Food: Meal Image Synthesis from IngredientsCode0
DR-GAN: Distribution Regularization for Text-to-Image GenerationCode0
On the Diversity of Realistic Image SynthesisCode0
Pose Guided Person Image GenerationCode0
On gradient regularizers for MMD GANsCode0
On Learning 3D Face Morphable Model from In-the-wild ImagesCode0
A DNN Optimizer that Improves over AdaBelief by Suppression of the Adaptive Stepsize RangeCode0
ArtAug: Enhancing Text-to-Image Generation through Synthesis-Understanding InteractionCode0
On GANs and GMMsCode0
One-shot Generative Domain Adaptation in 3D GANsCode0
Class-Splitting Generative Adversarial NetworksCode0
Array Camera Image Fusion using Physics-Aware TransformersCode0
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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