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 1501–1550 of 6689 papers

TitleStatusHype
Frequency Domain Image Translation: More Photo-realistic, Better Identity-preservingCode1
Controlling Style and Semantics in Weakly-Supervised Image GenerationCode1
Controlling Geometric Abstraction and Texture for Artistic ImagesCode1
Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual PerceptionCode1
Denoising Diffusion Autoencoders are Unified Self-supervised LearnersCode1
FreeGraftor: Training-Free Cross-Image Feature Grafting for Subject-Driven Text-to-Image GenerationCode1
Frido: Feature Pyramid Diffusion for Complex Scene Image SynthesisCode1
FPGAN-Control: A Controllable Fingerprint Generator for Training with Synthetic DataCode1
Frame Interpolation with Consecutive Brownian Bridge DiffusionCode1
FreCaS: Efficient Higher-Resolution Image Generation via Frequency-aware Cascaded SamplingCode1
A Unified Agentic Framework for Evaluating Conditional Image GenerationCode1
Latent Diffusion for Medical Image Segmentation: End to end learning for fast sampling and accuracyCode1
Differentially Private Diffusion ModelsCode1
Denoising Likelihood Score Matching for Conditional Score-based Data GenerationCode1
Denoising MCMC for Accelerating Diffusion-Based Generative ModelsCode1
LMM4LMM: Benchmarking and Evaluating Large-multimodal Image Generation with LMMsCode1
Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene GenerationCode1
Localized Concept Erasure for Text-to-Image Diffusion Models Using Training-Free Gated Low-Rank AdaptationCode1
A U-Net Based Discriminator for Generative Adversarial NetworksCode1
Controllable Person Image Synthesis with Spatially-Adaptive Warped NormalizationCode1
Dense Pixel-to-Pixel Harmonization via Continuous Image RepresentationCode1
DreamLCM: Towards High-Quality Text-to-3D Generation via Latent Consistency ModelCode1
Forward-only Diffusion Probabilistic ModelsCode1
Density estimation using Real NVPCode1
A disentangled generative model for disease decomposition in chest X-rays via normal image synthesisCode1
LoRA.rar: Learning to Merge LoRAs via Hypernetworks for Subject-Style Conditioned Image GenerationCode1
From Face to Natural Image: Learning Real Degradation for Blind Image Super-ResolutionCode1
GANs Can Play Lottery Tickets TooCode1
Controllable Person Image Synthesis with Attribute-Decomposed GANCode1
L-Verse: Bidirectional Generation Between Image and TextCode1
Interactive Character Control with Auto-Regressive Motion Diffusion ModelsCode1
DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion DelineationCode1
FooDI-ML: a large multi-language dataset of food, drinks and groceries images and descriptionsCode1
MADE: Masked Autoencoder for Distribution EstimationCode1
Controllable Mind Visual Diffusion ModelCode1
Focal Frequency Loss for Image Reconstruction and SynthesisCode1
BodyPressure -- Inferring Body Pose and Contact Pressure from a Depth ImageCode1
Foreground-Background Separation through Concept Distillation from Generative Image Foundation ModelsCode1
A Content Transformation Block For Image Style TransferCode1
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable ModelsCode1
Forget About the LiDAR: Self-Supervised Depth Estimators with MED Probability VolumesCode1
Markup-to-Image Diffusion Models with Scheduled SamplingCode1
Flow Contrastive Estimation of Energy-Based ModelsCode1
Controllable and Compositional Generation with Latent-Space Energy-Based ModelsCode1
Mask-conditioned latent diffusion for generating gastrointestinal polyp imagesCode1
ControlCom: Controllable Image Composition using Diffusion ModelCode1
3D-Aware Video GenerationCode1
Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion ModelsCode1
Contrastive Learning for Unpaired Image-to-Image TranslationCode1
AudioToken: Adaptation of Text-Conditioned Diffusion Models for Audio-to-Image GenerationCode1
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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