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 4951–5000 of 6689 papers

TitleStatusHype
StainDiffuser: MultiTask Dual Diffusion Model for Virtual Staining—0
STANLEY: Stochastic Gradient Anisotropic Langevin Dynamics for Learning Energy-Based Models—0
I3: Intent-Introspective Retrieval Conditioned on Instructions—0
ControlStyle: Text-Driven Stylized Image Generation Using Diffusion Priors—0
CASIA-Face-Africa: A Large-scale African Face Image Database—0
Cascading Modular Network (CAM-Net) for Multimodal Image Synthesis—0
Cascaded Diffusion Models for High Fidelity Image Generation—0
Convergence of Continuous Normalizing Flows for Learning Probability Distributions—0
Conversion Between CT and MRI Images Using Diffusion and Score-Matching Models—0
How far can we go with ImageNet for Text-to-Image generation?—0
CookGAN: Causality Based Text-to-Image Synthesis—0
A Diffusion-based Method for Multi-turn Compositional Image Generation—0
CookingDiffusion: Cooking Procedural Image Generation with Stable Diffusion—0
CoopInit: Initializing Generative Adversarial Networks via Cooperative Learning—0
Coordinate-Based Texture Inpainting for Pose-Guided Human Image Generation—0
CoProSketch: Controllable and Progressive Sketch Generation with Diffusion Model—0
Copula & Marginal Flows: Disentangling the Marginal from its Joint—0
Copyright-Aware Incentive Scheme for Generative Art Models Using Hierarchical Reinforcement Learning—0
CopyrightMeter: Revisiting Copyright Protection in Text-to-image Models—0
CopyrightShield: Spatial Similarity Guided Backdoor Defense against Copyright Infringement in Diffusion Models—0
CopyScope: Model-level Copyright Infringement Quantification in the Diffusion Workflow—0
CoRe: Context-Regularized Text Embedding Learning for Text-to-Image Personalization—0
State-of-the-Art in the Architecture, Methods and Applications of StyleGAN—0
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models—0
CorrDetail: Visual Detail Enhanced Self-Correction for Face Forgery Detection—0
State of the Art on Neural Rendering—0
Correlated discrete data generation using adversarial training—0
Correlation via Synthesis: End-to-end Image Generation and Radiogenomic Learning Based on Generative Adversarial Network—0
Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network—0
Correspondence Learning for Controllable Person Image Generation—0
Cosmetic-Aware Makeup Cleanser—0
Cost-Aware Routing for Efficient Text-To-Image Generation—0
CountDiffusion: Text-to-Image Synthesis with Training-Free Counting-Guidance Diffusion—0
Counter-Contrastive Learning for Language GANs—0
Statistical Test on Diffusion Model-based Anomaly Detection by Selective Inference—0
Stay on topic with Classifier-Free Guidance—0
Compact Scene Graphs for Layout Composition and Patch Retrieval—0
Counterfactual Image Generation for adversarially robust and interpretable Classifiers—0
Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markers—0
Counterfactuals and Uncertainty-Based Explainable Paradigm for the Automated Detection and Segmentation of Renal Cysts in Computed Tomography Images: A Multi-Center Study—0
Countering Personalized Text-to-Image Generation with Influence Watermarks—0
Counting Guidance for High Fidelity Text-to-Image Synthesis—0
Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators—0
Coupling Rendering and Generative Adversarial Networks for Artificial SAS Image Generation—0
COVID-19 CT Image Synthesis with a Conditional Generative Adversarial Network—0
CPGAN: Content-Parsing Generative Adversarial Networks for Text-to-Image Synthesis—0
CPR: Retrieval Augmented Generation for Copyright Protection—0
CRAFT: Cultural Russian-Oriented Dataset Adaptation for Focused Text-to-Image Generation—0
Crafting Parts for Expressive Object Composition—0
CRASH: Raw Audio Score-based Generative Modeling for Controllable High-resolution Drum Sound Synthesis—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