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 61516200 of 6689 papers

TitleStatusHype
Stochastic reconstruction of an oolitic limestone by generative adversarial networksCode0
Consistent Story Generation with Asymmetry Zigzag SamplingCode0
Knowledge-Aware Artifact Image Synthesis with LLM-Enhanced Prompting and Multi-Source SupervisionCode0
Fusion Embedding for Pose-Guided Person Image Synthesis with Diffusion ModelCode0
Stable Consistency Tuning: Understanding and Improving Consistency ModelsCode0
Multi-View Image-to-Image Translation Supervised by 3D PoseCode0
Disentangled Person Image GenerationCode0
Kosmos-G: Generating Images in Context with Multimodal Large Language ModelsCode0
Constrained CycleGAN for Effective Generation of Ultrasound Sector Images of Improved Spatial ResolutionCode0
Deformation equivariant cross-modality image synthesis with paired non-aligned training dataCode0
Cyclic 2.5D Perceptual Loss for Cross-Modal 3D Medical Image Synthesis: T1w MRI to Tau PETCode0
MUNBa: Machine Unlearning via Nash BargainingCode0
Kvasir-VQA: A Text-Image Pair GI Tract DatasetCode0
Cyclic image generation using chaotic dynamicsCode0
Murine AI excels at cats and cheese: Structural differences between human and mouse neurons and their implementation in generative AIsCode0
SAR TO OPTICAL IMAGE SYNTHESIS FOR CLOUD REMOVAL WITH GENERATIVE ADVERSARIAL NETWORKSCode0
Towards Pragmatic Semantic Image Synthesis for Urban ScenesCode0
Efficient Personalized Text-to-image Generation by Leveraging Textual SubspaceCode0
Private GANs, RevisitedCode0
LAION-5B: An open large-scale dataset for training next generation image-text modelsCode0
EDADepth: Enhanced Data Augmentation for Monocular Depth EstimationCode0
Private Synthetic Text Generation with Diffusion ModelsCode0
Scalable Adaptive Computation for Iterative GenerationCode0
GAN Dissection: Visualizing and Understanding Generative Adversarial NetworksCode0
GANetic Loss for Generative Adversarial Networks with a Focus on Medical ApplicationsCode0
GAN-GA: A Generative Model based on Genetic Algorithm for Medical Image GenerationCode0
Synthetic Medical Images from Dual Generative Adversarial NetworksCode0
Langevin Autoencoders for Learning Deep Latent Variable ModelsCode0
Mutually improved endoscopic image synthesis and landmark detection in unpaired image-to-image translationCode0
Language-based Colorization of Scene SketchesCode0
Language Guided Adversarial PurificationCode0
GANs for Biological Image SynthesisCode0
Probabilistic Neural Programmed Networks for Scene GenerationCode0
Neural Monge Map estimation and its applicationsCode0
ProbGAN: Towards Probabilistic GAN with Theoretical GuaranteesCode0
Visual Object Networks: Image Generation with Disentangled 3D RepresentationCode0
D^2iT: Dynamic Diffusion Transformer for Accurate Image GenerationCode0
Abstract Art Interpretation Using ControlNetCode0
Context-Aware Compilation of DNN Training Pipelines across Edge and CloudCode0
GAN You Do the GAN GAN?Code0
Wavelet-based Unsupervised Label-to-Image TranslationCode0
Spanish TrOCR: Leveraging Transfer Learning for Language AdaptationCode0
DeLiGAN : Generative Adversarial Networks for Diverse and Limited DataCode0
Bayesian CP Factorization of Incomplete Tensors with Automatic Rank DeterminationCode0
Surrealistic-like Image Generation with Vision-Language ModelsCode0
Laplacian-Steered Neural Style TransferCode0
Professor Forcing: A New Algorithm for Training Recurrent NetworksCode0
Towards Safe Synthetic Image Generation On the Web: A Multimodal Robust NSFW Defense and Million Scale DatasetCode0
Scaling Autoregressive Models for Content-Rich Text-to-Image GenerationCode0
Affect-Conditioned Image GenerationCode0
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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