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 5751–5800 of 6689 papers

TitleStatusHype
Evaluating the Impact of Intensity Normalization on MR Image SynthesisCode0
Unsupervised Person Image Generation with Semantic Parsing TransformationCode0
Adversarial symmetric GANs: bridging adversarial samples and adversarial networksCode0
Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated ImageryCode0
Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial NetworksCode0
Composite Functional Gradient Learning of Generative Adversarial ModelsCode0
Shadow Removal by High-Quality Shadow SynthesisCode0
Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational AutoencodersCode0
EvoGAN: An Evolutionary Computation Assisted GANCode0
TaxaDiffusion: Progressively Trained Diffusion Model for Fine-Grained Species GenerationCode0
Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out CodesCode0
DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences SynthesisCode0
Perceptual Gradient NetworksCode0
Exploration into Translation-Equivariant Image QuantizationCode0
Table and Image Generation for Investigating Knowledge of Entities in Pre-trained Vision and Language ModelsCode0
Breaking Free: How to Hack Safety Guardrails in Black-Box Diffusion Models!Code0
Medical Image Fusion for High-Level Analysis: A Mutual Enhancement Framework for Unaligned PAT and MRICode0
Exact Fusion via Feature Distribution Matching for Few-shot Image GenerationCode0
Image Translation for Medical Image Generation -- Ischemic Stroke LesionsCode0
VTNFP: An Image-Based Virtual Try-On Network With Body and Clothing Feature PreservationCode0
Meta-Learning and Self-Supervised Pretraining for Real World Image TranslationCode0
Reproducibility Study of "ITI-GEN: Inclusive Text-to-Image Generation"Code0
Imaginative Walks: Generative Random Walk Deviation Loss for Improved Unseen Learning RepresentationCode0
IMAGINE-E: Image Generation Intelligence Evaluation of State-of-the-art Text-to-Image ModelsCode0
Example-Guided Style Consistent Image Synthesis from Semantic LabelingCode0
Composition and Deformance: Measuring Imageability with a Text-to-Image ModelCode0
TRB: A Novel Triplet Representation for Understanding 2D Human BodyCode0
Persistently Trained, Diffusion-assisted Energy-based ModelsCode0
Experimental Quantum Generative Adversarial Networks for Image GenerationCode0
Deep Generative Modeling with Backward Stochastic Differential EquationsCode0
Expertise elevates AI usage: experimental evidence comparing laypeople and professional artistsCode0
Repulsive Latent Score Distillation for Solving Inverse ProblemsCode0
Explainable Deep Learning: A Visual Analytics Approach with Transition MatricesCode0
Metrics that matter: Evaluating image quality metrics for medical image generationCode0
Implementing Adaptations for Vision AutoRegressive ModelCode0
Implementing and Experimenting with Diffusion Models for Text-to-Image GenerationCode0
Adversarial Feedback LoopCode0
Implicit competitive regularization in GANsCode0
Explicitly Representing Syntax Improves Sentence-to-layout Prediction of Unexpected SituationsCode0
Explicit Temporal Embedding in Deep Generative Latent Models for Longitudinal Medical Image SynthesisCode0
Personalized Image Generation for Color Vision Deficiency PopulationCode0
Implicit Dynamical Flow Fusion (IDFF) for Generative ModelingCode0
Implicit Generation and Modeling with Energy Based ModelsCode0
Implicit Generative CopulasCode0
Implicit Inversion turns CLIP into a DecoderCode0
MFGDiffusion: Mask-Guided Smoke Synthesis for Enhanced Forest Fire DetectionCode0
MFTF: Mask-free Training-free Object Level Layout Control Diffusion ModelCode0
An Empirical Study and Analysis of Text-to-Image Generation Using Large Language Model-Powered Textual RepresentationCode0
Exploring DeshuffleGANs in Self-Supervised Generative Adversarial NetworksCode0
Coarse-to-Fine Gaze Redirection with Numerical and Pictorial GuidanceCode0
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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