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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 751–800 of 6689 papers

TitleStatusHype
Accelerating Score-based Generative Models with Preconditioned Diffusion SamplingCode1
Learning to Generate Levels From NothingCode1
DiG-IN: Diffusion Guidance for Investigating Networks - Uncovering Classifier Differences Neuron Visualisations and Visual Counterfactual ExplanationsCode1
2D medical image synthesis using transformer-based denoising diffusion probabilistic modelCode1
DIG In: Evaluating Disparities in Image Generations with Indicators for Geographic DiversityCode1
A Scene-Text Synthesis Engine Achieved Through Learning from Decomposed Real-World DataCode1
AdvPaint: Protecting Images from Inpainting Manipulation via Adversarial Attention DisruptionCode1
DiffX: Guide Your Layout to Cross-Modal Generative ModelingCode1
Fully Spiking Denoising Diffusion Implicit ModelsCode1
Fuzzy-Conditioned Diffusion and Diffusion Projection Attention Applied to Facial Image CorrectionCode1
Accelerating Parallel Sampling of Diffusion ModelsCode1
Causal Inference via Style Transfer for Out-of-distribution GeneralisationCode1
AdvI2I: Adversarial Image Attack on Image-to-Image Diffusion modelsCode1
ArtNeRF: A Stylized Neural Field for 3D-Aware Cartoonized Face SynthesisCode1
Full-Glow: Fully conditional Glow for more realistic image generationCode1
Artistic Glyph Image Synthesis via One-Stage Few-Shot LearningCode1
Diffusion Probabilistic Modeling for Video GenerationCode1
From Image to Imuge: Immunized Image GenerationCode1
CoCosNet v2: Full-Resolution Correspondence Learning for Image TranslationCode1
Diffusion Models With Learned Adaptive NoiseCode1
Frequency Domain Image Translation: More Photo-realistic, Better Identity-preservingCode1
Memory-Efficient 3D Denoising Diffusion Models for Medical Image ProcessingCode1
Accelerating Markov Chain Monte Carlo sampling with diffusion modelsCode1
Frido: Feature Pyramid Diffusion for Complex Scene Image SynthesisCode1
ArtiFact: A Large-Scale Dataset with Artificial and Factual Images for Generalizable and Robust Synthetic Image DetectionCode1
Diffusion Models for Constrained DomainsCode1
Diffusion Self-Guidance for Controllable Image GenerationCode1
Diffusion Models for Interferometric Satellite Aperture RadarCode1
Diffusion Normalizing FlowCode1
Discrete Contrastive Diffusion for Cross-Modal Music and Image GenerationCode1
From Face to Natural Image: Learning Real Degradation for Blind Image Super-ResolutionCode1
Fully automatic computer-aided mass detection and segmentation via pseudo-color mammograms and Mask R-CNNCode1
Adversarial score matching and improved sampling for image generationCode1
Accelerating Guided Diffusion Sampling with Splitting Numerical MethodsCode1
Diffusion Model is Secretly a Training-free Open Vocabulary Semantic SegmenterCode1
Frame Interpolation with Consecutive Brownian Bridge DiffusionCode1
Diffusion in Diffusion: Cyclic One-Way Diffusion for Text-Vision-Conditioned GenerationCode1
FreCaS: Efficient Higher-Resolution Image Generation via Frequency-aware Cascaded SamplingCode1
Accelerating Diffusion Transformer via Increment-Calibrated Caching with Channel-Aware Singular Value DecompositionCode1
Diffusion Models Are Innate One-Step GeneratorsCode1
FreeGraftor: Training-Free Cross-Image Feature Grafting for Subject-Driven Text-to-Image GenerationCode1
Diffusion Features to Bridge Domain Gap for Semantic SegmentationCode1
Adversarial Nibbler: An Open Red-Teaming Method for Identifying Diverse Harms in Text-to-Image GenerationCode1
ARINAR: Bi-Level Autoregressive Feature-by-Feature Generative ModelsCode1
Accelerating Diffusion Sampling with Optimized Time StepsCode1
Diffusion Models Beat GANs on Image ClassificationCode1
Manifold Matching via Deep Metric Learning for Generative ModelingCode1
Benchmarking Robustness of Multimodal Image-Text Models under Distribution ShiftCode1
DiffusionFace: Towards a Comprehensive Dataset for Diffusion-Based Face Forgery AnalysisCode1
Freestyle Layout-to-Image SynthesisCode1
Show:102550
← PrevPage 16 of 134Next →
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