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

Showing 801850 of 6689 papers

TitleStatusHype
Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNNCode1
Fully Spiking Denoising Diffusion Implicit ModelsCode1
FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space OptimizationCode1
GANs Can Play Lottery Tickets TooCode1
SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear LayerCode1
Are Diffusion Models Vulnerable to Membership Inference Attacks?Code1
Are Diffusion Models Vision-And-Language Reasoners?Code1
From Face to Natural Image: Learning Real Degradation for Blind Image Super-ResolutionCode1
From Image to Imuge: Immunized Image GenerationCode1
Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANsCode1
Freestyle Layout-to-Image SynthesisCode1
Frequency Domain Image Translation: More Photo-realistic, Better Identity-preservingCode1
AR-Diffusion: Auto-Regressive Diffusion Model for Text GenerationCode1
Accelerating Diffusion Models via Early Stop of the Diffusion ProcessCode1
Frido: Feature Pyramid Diffusion for Complex Scene Image SynthesisCode1
Causal Inference via Style Transfer for Out-of-distribution GeneralisationCode1
FreCaS: Efficient Higher-Resolution Image Generation via Frequency-aware Cascaded SamplingCode1
Frame Interpolation with Consecutive Brownian Bridge DiffusionCode1
FPGAN-Control: A Controllable Fingerprint Generator for Training with Synthetic DataCode1
Arbitrary-Scale Image SynthesisCode1
Cloud Removal in Satellite Images Using Spatiotemporal Generative NetworksCode1
Accelerate TarFlow Sampling with GS-Jacobi IterationCode1
FreeGraftor: Training-Free Cross-Image Feature Grafting for Subject-Driven Text-to-Image GenerationCode1
Full-Glow: Fully conditional Glow for more realistic image generationCode1
GANSeg: Learning to Segment by Unsupervised Hierarchical Image GenerationCode1
Generative Occupancy Fields for 3D Surface-Aware Image SynthesisCode1
FooDI-ML: a large multi-language dataset of food, drinks and groceries images and descriptionsCode1
Foreground-Background Separation through Concept Distillation from Generative Image Foundation ModelsCode1
CLIP-VQDiffusion : Langauge Free Training of Text To Image generation using CLIP and vector quantized diffusion modelCode1
Adversarial Image Generation by Spatial Transformation in Perceptual ColorspacesCode1
Clockwork Diffusion: Efficient Generation With Model-Step DistillationCode1
Forget About the LiDAR: Self-Supervised Depth Estimators with MED Probability VolumesCode1
A Preliminary Study for GPT-4o on Image RestorationCode1
CLoG: Benchmarking Continual Learning of Image Generation ModelsCode1
Focal Frequency Loss for Image Reconstruction and SynthesisCode1
Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion ModelsCode1
Approaching Deep Learning through the Spectral Dynamics of WeightsCode1
Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion ModelsCode1
Applications of Deep Learning in Fundus Images: A ReviewCode1
AccDiffusion v2: Towards More Accurate Higher-Resolution Diffusion ExtrapolationCode1
Adversarial Generation of Continuous ImagesCode1
Flow Contrastive Estimation of Energy-Based ModelsCode1
FBSDiff: Plug-and-Play Frequency Band Substitution of Diffusion Features for Highly Controllable Text-Driven Image TranslationCode1
ForkGAN: Seeing into the Rainy NightCode1
FlexDiT: Dynamic Token Density Control for Diffusion TransformerCode1
CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIPCode1
FlexiFilm: Long Video Generation with Flexible ConditionsCode1
Finite Scalar Quantization: VQ-VAE Made SimpleCode1
First Creating Backgrounds Then Rendering Texts: A New Paradigm for Visual Text BlendingCode1
Diffusion-NPO: Negative Preference Optimization for Better Preference Aligned Generation of Diffusion ModelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Improved DDPMFID12.3Unverified
2ADMFID11.84Unverified
3BigGAN-deepFID8.1Unverified
4Polarity-BigGANFID6.82Unverified
5VQGAN+Transformer (k=mixed, p=1.0, a=0.005)FID6.59Unverified
6MaskGITFID6.18Unverified
7VQGAN+Transformer (k=600, p=1.0, a=0.05)FID5.2Unverified
8CDMFID4.88Unverified
9ADM-GFID4.59Unverified
10RINFID4.51Unverified
#ModelMetricClaimedVerifiedStatus
1PresGANFID52.2Unverified
2RESFLOWFID48.29Unverified
3Residual FlowFID46.37Unverified
4GLF+perceptual loss (ours)FID44.6Unverified
5ProdPoly no activation functionsFID40.45Unverified
6ProdPoly no activation functionsFID36.77Unverified
7ACGANFID35.47Unverified
8DenseFlow-74-10FID34.9Unverified
9NVAE w/ flowFID32.53Unverified
10QSNGANFID31.97Unverified
#ModelMetricClaimedVerifiedStatus
1GLIDE + CLSFID30.87Unverified
2GLIDE + CLIPFID30.46Unverified
3GLIDE + CLS-FREEFID29.22Unverified
4GLIDE + CLIP + CLS + CLS-FREEFID29.18Unverified
5PGMGANFID21.73Unverified
6CLR-GANFID20.27Unverified
7FMFID14.45Unverified
8CT (Direct Generation, NFE=1)FID13Unverified
9CT (Direct Generation, NFE=2)FID11.1Unverified
10GLIDE +CLSKID7.95Unverified