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 25512575 of 6689 papers

TitleStatusHype
MFGDiffusion: Mask-Guided Smoke Synthesis for Enhanced Forest Fire DetectionCode0
Data-driven Crop Growth Simulation on Time-varying Generated Images using Multi-conditional Generative Adversarial NetworksCode0
The Role of Data Curation in Image CaptioningCode0
Megapixel Image Generation with Step-Unrolled Denoising AutoencodersCode0
BEGAN: Boundary Equilibrium Generative Adversarial NetworksCode0
Semantic Object Accuracy for Generative Text-to-Image SynthesisCode0
DAMM-Diffusion: Learning Divergence-Aware Multi-Modal Diffusion Model for Nanoparticles Distribution PredictionCode0
Medical Image Synthesis with Deep Convolutional Adversarial NetworksCode0
Learning Energy-Based Models With Adversarial TrainingCode0
Medical Imaging Complexity and its Effects on GAN PerformanceCode0
MFTF: Mask-free Training-free Object Level Layout Control Diffusion ModelCode0
MC-GAN: Multi-conditional Generative Adversarial Network for Image SynthesisCode0
D^2iT: Dynamic Diffusion Transformer for Accurate Image GenerationCode0
MC^2: Multi-concept Guidance for Customized Multi-concept GenerationCode0
Measurement Score-Based Diffusion ModelCode0
Cyclic image generation using chaotic dynamicsCode0
Cyclic 2.5D Perceptual Loss for Cross-Modal 3D Medical Image Synthesis: T1w MRI to Tau PETCode0
Bayesian CP Factorization of Incomplete Tensors with Automatic Rank DeterminationCode0
M-EBM: Towards Understanding the Manifolds of Energy-Based ModelsCode0
Cycle-Consistent Generative Rendering for 2D-3D Modality TranslationCode0
Batch-Instructed Gradient for Prompt Evolution:Systematic Prompt Optimization for Enhanced Text-to-Image SynthesisCode0
Adaptive Consensus Optimization Method for GANsCode0
Mask Embedding in conditional GAN for Guided Synthesis of High Resolution ImagesCode0
Mapping Instructions to Actions in 3D Environments with Visual Goal PredictionCode0
CusConcept: Customized Visual Concept Decomposition with Diffusion ModelsCode0
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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