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 1851–1900 of 6689 papers

TitleStatusHype
Efficient Semantic Image Synthesis via Class-Adaptive NormalizationCode1
UnrealPerson: An Adaptive Pipeline towards Costless Person Re-identificationCode1
You Only Need Adversarial Supervision for Semantic Image SynthesisCode1
TediGAN: Text-Guided Diverse Face Image Generation and ManipulationCode1
Adaptive Weighted Discriminator for Training Generative Adversarial NetworksCode1
Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar ReconstructionCode1
Spectral Distribution Aware Image GenerationCode1
Learning Two-Stream CNN for Multi-Modal Age-related Macular Degeneration CategorizationCode1
CoCosNet v2: Full-Resolution Correspondence Learning for Image TranslationCode1
Improved Contrastive Divergence Training of Energy Based ModelsCode1
pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image SynthesisCode1
Refining Deep Generative Models via Discriminator Gradient FlowCode1
Learning Semantic-aware Normalization for Generative Adversarial NetworksCode1
S2FGAN: Semantically Aware Interactive Sketch-to-Face TranslationCode1
Overcoming Barriers to Data Sharing with Medical Image Generation: A Comprehensive EvaluationCode1
Hijack-GAN: Unintended-Use of Pretrained, Black-Box GANsCode1
Frequency Domain Image Translation: More Photo-realistic, Better Identity-preservingCode1
Image Generators with Conditionally-Independent Pixel SynthesisCode1
Omni-GAN: On the Secrets of cGANs and BeyondCode1
Score-Based Generative Modeling through Stochastic Differential EquationsCode1
Adversarial Generation of Continuous ImagesCode1
HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color HistogramsCode1
Synthesizing Optical and SAR Imagery From Land Cover Maps and Auxiliary Raster DataCode1
Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on ImagesCode1
MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image GenerationCode1
Continuous Conditional Generative Adversarial Networks: Novel Empirical Losses and Label Input MechanismsCode1
Text-to-Image Generation Grounded by Fine-Grained User AttentionCode1
Towards Disentangling Latent Space for Unsupervised Semantic Face EditingCode1
CooGAN: A Memory-Efficient Framework for High-Resolution Facial Attribute EditingCode1
Enhanced Balancing GAN: Minority-class Image GenerationCode1
MichiGAN: Multi-Input-Conditioned Hair Image Generation for Portrait EditingCode1
Generative Neurosymbolic MachinesCode1
Few-Shot Adaptation of Generative Adversarial NetworksCode1
One Model to Reconstruct Them All: A Novel Way to Use the Stochastic Noise in StyleGANCode1
Synthesis of COVID-19 Chest X-rays using Unpaired Image-to-Image TranslationCode1
Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 NetworkCode1
Resolution Dependent GAN Interpolation for Controllable Image Synthesis Between DomainsCode1
Image Generation With Neural Cellular AutomatasCode1
Deep-Masking Generative Network: A Unified Framework for Background Restoration from Superimposed ImagesCode1
Evaluating the Clinical Realism of Synthetic Chest X-Rays Generated Using Progressively Growing GANsCode1
A disentangled generative model for disease decomposition in chest X-rays via normal image synthesisCode1
Data Augmentation Based Malware Detection using Convolutional Neural NetworksCode1
Improving Relational Regularized Autoencoders with Spherical Sliced Fused Gromov WassersteinCode1
Implicit Rank-Minimizing AutoencoderCode1
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based ModelsCode1
RG-Flow: A hierarchical and explainable flow model based on renormalization group and sparse priorCode1
TinyGAN: Distilling BigGAN for Conditional Image GenerationCode1
X-LXMERT: Paint, Caption and Answer Questions with Multi-Modal TransformersCode1
DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific DeltaCode1
Multi-Spectral Image Synthesis for Crop/Weed Segmentation in Precision FarmingCode1
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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