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 5301–5350 of 6689 papers

TitleStatusHype
HessianFR: An Efficient Hessian-based Follow-the-Ridge Algorithm for Minimax Optimization—0
A SSIM Guided cGAN Architecture For Clinically Driven Generative Image Synthesis of Multiplexed Spatial Proteomics Channels—0
Generation of Artificial CT Images using Patch-based Conditional Generative Adversarial NetworksCode0
Computerized Tomography Pulmonary Angiography Image Simulation using Cycle Generative Adversarial Network from Chest CT imaging in Pulmonary Embolism Patients—0
Covid-19 chest x-ray image generation using resnet-dcgan modelCode0
StyLandGAN: A StyleGAN based Landscape Image Synthesis using Depth-map—0
The Effectiveness of Temporal Dependency in Deepfake Video Detection—0
Ray Priors through Reprojection: Improving Neural Radiance Fields for Novel View Extrapolation—0
D3T-GAN: Data-Dependent Domain Transfer GANs for Few-shot Image Generation—0
Transformer-based Cross-Modal Recipe Embeddings with Large Batch Training—0
On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models—0
A Closer Look at Few-shot Image Generation—0
High-Resolution UAV Image Generation for Sorghum Panicle Detection—0
GAN-Based Multi-View Video Coding with Spatio-Temporal EPI Reconstruction—0
Text to artistic image generationCode0
DeepPortraitDrawing: Generating Human Body Images from Freehand Sketches—0
BiOcularGAN: Bimodal Synthesis and Annotation of Ocular ImagesCode0
A Comprehensive Survey of Image Augmentation Techniques for Deep Learning—0
DANBO: Disentangled Articulated Neural Body Representations via Graph Neural Networks—0
Seeding Diversity into AI Art—0
Language-agnostic Semantic Consistent Text-to-Image Generation—0
Augmentation Techniques Analysis with Removal of Class Imbalance Using PyTorch for Intel Scene Dataset—0
Augmented Balanced Image Dataset Generator Using AugStatic LibraryCode0
Improving Model Performance and Removing the Class Imbalance Problem Using Augmentation—0
Resnet18 Model With Sequential Layer For Computing Accuracy On Image Classification Dataset—0
AugStatic - A Light-Weight Image Augmentation LibraryCode0
One Model to Synthesize Them All: Multi-contrast Multi-scale Transformer for Missing Data Imputation—0
Self-Supervised Text Erasing with Controllable Image Synthesis—0
Optimized latent-code selection for explainable conditional text-to-image GANs—0
Assessing the ability of generative adversarial networks to learn canonical medical image statistics—0
Transfer Learning from Synthetic In-vitro Soybean Pods Dataset for In-situ Segmentation of On-branch Soybean Pod—0
Reinforcing Generated Images via Meta-learning for One-Shot Fine-Grained Visual Recognition—0
DAM-GAN : Image Inpainting using Dynamic Attention Map based on Fake Texture Detection—0
A Taxonomy of Prompt Modifiers for Text-To-Image Generation—0
A Comprehensive Survey on Data-Efficient GANs in Image Generation—0
Simultaneous Multiple-Prompt Guided Generation Using Differentiable Optimal Transport—0
StyleT2F: Generating Human Faces from Textual Description Using StyleGAN2Code0
DR-GAN: Distribution Regularization for Text-to-Image GenerationCode0
Guided Co-Modulated GAN for 360° Field of View Extrapolation—0
Sketch guided and progressive growing GAN for realistic and editable ultrasound image synthesis—0
ManiTrans: Entity-Level Text-Guided Image Manipulation via Token-wise Semantic Alignment and GenerationCode0
Noise-based Enhancement for Foveated Rendering—0
Practical Digital Disguises: Leveraging Face Swaps to Protect Patient Privacy—0
Evaluating Procedures for Establishing Generative Adversarial Network-based Stochastic Image Models in Medical Imaging—0
KNN-Diffusion: Image Generation via Large-Scale Retrieval—0
The Swiss Army Knife for Image-to-Image Translation: Multi-Task Diffusion Models—0
Thermal to Visible Image Synthesis under Atmospheric Turbulence—0
DT2I: Dense Text-to-Image Generation from Region Descriptions—0
3D microstructural generation from 2D images of cement paste using generative adversarial networksCode0
Flexible Portrait Image Editing with Fine-Grained Control—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