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 3776–3800 of 6689 papers

TitleStatusHype
VM-DDPM: Vision Mamba Diffusion for Medical Image Synthesis—0
A Survey on Personalized Content Synthesis with Diffusion Models—0
Discrepancy-based Diffusion Models for Lesion Detection in Brain MRI—0
FlexEControl: Flexible and Efficient Multimodal Control for Text-to-Image Generation—0
Diffusion-HMC: Parameter Inference with Diffusion-model-driven Hamiltonian Monte CarloCode0
HAGAN: Hybrid Augmented Generative Adversarial Network for Medical Image Synthesis—0
Variational Schrödinger Diffusion Models—0
Simple Drop-in LoRA Conditioning on Attention Layers Will Improve Your Diffusion Model—0
ResNCT: A Deep Learning Model for the Synthesis of Nephrographic Phase Images in CT Urography—0
TexControl: Sketch-Based Two-Stage Fashion Image Generation Using Diffusion Model—0
Diffusion-driven GAN Inversion for Multi-Modal Face Image GenerationCode0
Generated Contents Enrichment—0
Data-Efficient Molecular Generation with Hierarchical Textual InversionCode0
Multi-method Integration with Confidence-based Weighting for Zero-shot Image Classification—0
Defect Image Sample Generation With Diffusion Prior for Steel Surface Defect Recognition—0
Functional Imaging Constrained Diffusion for Brain PET Synthesis from Structural MRICode0
Long Tail Image Generation Through Feature Space Augmentation and Iterated LearningCode0
Towards Inclusive Face Recognition Through Synthetic Ethnicity Alteration—0
Improving Subject-Driven Image Synthesis with Subject-Agnostic Guidance—0
RGBX: Image decomposition and synthesis using material- and lighting-aware diffusion models—0
Guided Conditional Diffusion Classifier (ConDiff) for Enhanced Prediction of Infection in Diabetic Foot Ulcers—0
UWAFA-GAN: Ultra-Wide-Angle Fluorescein Angiography Transformation via Multi-scale Generation and Registration EnhancementCode0
Compressive Sensing Imaging Using Caustic Lens Mask Generated by Periodic Perturbation in a Ripple Tank—0
SonicDiffusion: Audio-Driven Image Generation and Editing with Pretrained Diffusion Models—0
Streamlining Image Editing with Layered Diffusion Brushes—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