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 6101–6150 of 6689 papers

TitleStatusHype
Intelligent image synthesis to attack a segmentation CNN using adversarial learning—0
Subsampling Generative Adversarial Networks: Density Ratio Estimation in Feature Space with Softplus LossCode0
Human Synthesis and Scene Compositing—0
Variational Conditional GAN for Fine-grained Controllable Image Generation—0
Fourier-CPPNs for Image Synthesis—0
Synthetic CT Generation from MRI Using Improved DualGAN—0
Triplet-Aware Scene Graph Embeddings—0
Controllable Text-to-Image GenerationCode0
Coupling Rendering and Generative Adversarial Networks for Artificial SAS Image Generation—0
FakeSpotter: A Simple yet Robust Baseline for Spotting AI-Synthesized Fake Faces—0
ρ-VAE: Autoregressive parametrization of the VAE encoderCode0
Inducing Hierarchical Compositional Model by Sparsifying Generator Network—0
Learning Priors for Adversarial Autoencoders—0
One-to-one Mapping for Unpaired Image-to-image Translation—0
Towards Learning a Self-inverse Network for Bidirectional Image-to-image Translation—0
An Acceleration Framework for High Resolution Image Synthesis—0
TorchGAN: A Flexible Framework for GAN Training and EvaluationCode0
Testing Deep Learning Models for Image Analysis Using Object-Relevant Metamorphic Relations—0
Relationship-Aware Spatial Perception Fusion for Realistic Scene Layout Generation—0
BooVAE: Boosting Approach for Continual Learning of VAECode0
Systematic Analysis of Image Generation using GANs—0
Flexible Conditional Image Generation of Missing Data with Learned Mental Maps—0
EEG Signal Dimensionality Reduction and Classification using Tensor Decomposition and Deep Convolutional Neural Networks—0
PixelVAE++: Improved PixelVAE with Discrete Prior—0
Sequential Adversarial Learning for Self-Supervised Deep Visual Odometry—0
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality TransferCode0
Fully Automated Image De-fencing using Conditional Generative Adversarial Networks—0
Unpaired Image-to-Speech Synthesis with Multimodal Information BottleneckCode0
Dual Adversarial Inference for Text-to-Image Synthesis—0
AutoGAN: Neural Architecture Search for Generative Adversarial NetworksCode0
Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance—0
Editing Text in the WildCode0
Relighting Humans: Occlusion-Aware Inverse Rendering for Full-Body Human Images—0
SkrGAN: Sketching-rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis—0
Visual-Relation Conscious Image Generation from Structured-Text—0
InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations—0
Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation—0
An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation—0
Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement—0
A Two Stage GAN for High Resolution Retinal Image Generation and Segmentation—0
Variational f-divergence Minimization—0
Latent Space Factorisation and Manipulation via Matrix Subspace ProjectionCode0
Discriminative Consistent Domain Generation for Semi-supervised Learning—0
Warp and Learn: Novel Views Generation for Vehicles and Other ObjectsCode0
Lifelong GAN: Continual Learning for Conditional Image Generation—0
MintNet: Building Invertible Neural Networks with Masked ConvolutionsCode0
SynthText3D: Synthesizing Scene Text Images from 3D Virtual WorldsCode0
Adversarial Lipschitz RegularizationCode0
Jointly Adversarial Network to Wavelength Compensation and Dehazing of Underwater Images—0
M3D-GAN: Multi-Modal Multi-Domain Translation with Universal Attention—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