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 5801–5850 of 6689 papers

TitleStatusHype
Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator—0
CellCycleGAN: Spatiotemporal Microscopy Image Synthesis of Cell Populations using Statistical Shape Models and Conditional GANs—0
LT-GAN: Self-Supervised GAN with Latent Transformation Detection—0
Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational AutoencodersCode0
Training Generative Adversarial Networks via stochastic Nash games—0
Semantic Editing On Segmentation Map Via Multi-Expansion Loss—0
New Ideas and Trends in Deep Multimodal Content Understanding: A Review—0
A Human Eye-based Text Color Scheme Generation Method for Image Synthesis—0
The power of pictures: using ML assisted image generation to engage the crowd in complex socioscientific problems—0
Random Network Distillation as a Diversity Metric for Both Image and Text Generation—0
Experimental Quantum Generative Adversarial Networks for Image GenerationCode0
Omni-Directional Image Generation from Single Snapshot ImageCode0
Memory-efficient GAN-based Domain Translation of High Resolution 3D Medical Images—0
Arbitrary Style Transfer using Graph Instance Normalization—0
A Contrastive Learning Approach for Training Variational Autoencoder Priors—0
Image Translation for Medical Image Generation -- Ischemic Stroke LesionsCode0
Generating Gameplay-Relevant Art Assets with Transfer LearningCode0
MGD-GAN: Text-to-Pedestrian generation through Multi-Grained Discrimination—0
Tabular GANs for uneven distributionCode0
EEG to fMRI Synthesis: Is Deep Learning a candidate?—0
Simplifying Models with Unlabeled Output Data—0
Data Instance Prior for Transfer Learning in GANs—0
Scene Graph to Image Generation with Contextualized Object Layout Refinement—0
Triple-GAN with Variable Fractional Order Gradient Descent Method and Mish Activation Function—0
Adversarial Rain Attack and Defensive Deraining for DNN Perception—0
Dodging DeepFake Detection via Implicit Spatial-Domain Notch Filtering—0
Synthetic Convolutional Features for Improved Semantic Segmentation—0
Conditional Image Generation with One-Vs-All Classifier—0
TreeGAN: Incorporating Class Hierarchy into Image Generation—0
Deep Sinogram Completion with Image Prior for Metal Artifact Reduction in CT Images—0
Conditional Spoken Digit Generation with StyleGAN—0
not-so-BigGAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution—0
Improved Modeling of 3D Shapes with Multi-view Depth MapsCode0
TiVGAN: Text to Image to Video Generation with Step-by-Step Evolutionary Generator—0
Simulation of an Elevator Group Control Using Generative Adversarial Networks and Related AI Tools—0
Decontextualized learning for interpretable hierarchical representations of visual patternsCode0
On the Intrinsic Robustness of NVM Crossbars Against Adversarial Attacks—0
Causal Adversarial Network for Learning Conditional and Interventional Distributions—0
CA-GAN: Weakly Supervised Color Aware GAN for Controllable Makeup Transfer—0
Perceptual underwater image enhancement with deep learning and physical priors—0
Causal Future Prediction in a Minkowski Space-Time—0
Improving Text to Image Generation using Mode-seeking Function—0
Self-Supervised Ultrasound to MRI Fetal Brain Image SynthesisCode0
A New Perspective on Stabilizing GANs training: Direct Adversarial TrainingCode0
Person image generation with semantic attention network for person re-identification—0
Category Level Object Pose Estimation via Neural Analysis-by-Synthesis—0
Audio Dequantization for High Fidelity Audio Generation in Flow-based Neural Vocoder—0
Uncertainty Quantification using Variational Inference for Biomedical Image SegmentationCode0
Implanting Synthetic Lesions for Improving Liver Lesion Segmentation in CT Exams—0
Multimodal Image-to-Image Translation via Mutual Information Estimation and Maximization—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