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 826850 of 6689 papers

TitleStatusHype
PIXELS: Progressive Image Xemplar-based Editing with Latent SurgeryCode1
Multimodal LLMs Can Reason about Aesthetics in Zero-ShotCode1
Generative diffusion model with inverse renormalization group flowsCode1
D^2-DPM: Dual Denoising for Quantized Diffusion Probabilistic ModelsCode1
Face-MakeUp: Multimodal Facial Prompts for Text-to-Image GenerationCode1
ImagineFSL: Self-Supervised Pretraining Matters on Imagined Base Set for VLM-based Few-shot LearningCode1
Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual ApproximatorsCode1
Anatomical Consistency and Adaptive Prior-informed Transformation for Multi-contrast MR Image Synthesis via Diffusion ModelCode1
Zero-Shot Image Restoration Using Few-Step Guidance of Consistency Models (and Beyond)Code1
FairDiffusion: Enhancing Equity in Latent Diffusion Models via Fair Bayesian PerturbationCode1
Extract Free Dense Misalignment from CLIPCode1
BS-LDM: Effective Bone Suppression in High-Resolution Chest X-Ray Images with Conditional Latent Diffusion ModelsCode1
PersonaMagic: Stage-Regulated High-Fidelity Face Customization with Tandem EquilibriumCode1
Relation-Guided Adversarial Learning for Data-free Knowledge TransferCode1
IDProtector: An Adversarial Noise Encoder to Protect Against ID-Preserving Image GenerationCode1
3D^2-Actor: Learning Pose-Conditioned 3D-Aware Denoiser for Realistic Gaussian Avatar ModelingCode1
Grid: Omni Visual GenerationCode1
Fast Prompt Alignment for Text-to-Image GenerationCode1
ACDiT: Interpolating Autoregressive Conditional Modeling and Diffusion TransformerCode1
Precise, Fast, and Low-cost Concept Erasure in Value Space: Orthogonal Complement MattersCode1
FlexDiT: Dynamic Token Density Control for Diffusion TransformerCode1
BiDM: Pushing the Limit of Quantization for Diffusion ModelsCode1
LoRA.rar: Learning to Merge LoRAs via Hypernetworks for Subject-Style Conditioned Image GenerationCode1
MRGen: Diffusion-based Controllable Data Engine for MRI Segmentation towards Unannotated ModalitiesCode1
PatchDPO: Patch-level DPO for Finetuning-free Personalized Image GenerationCode1
Show:102550
← PrevPage 34 of 268Next →

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