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 151200 of 6689 papers

TitleStatusHype
Elucidating the Design Space of Diffusion-Based Generative ModelsCode4
High-Resolution Image Synthesis with Latent Diffusion ModelsCode4
ControlVAE: Tuning, Analytical Properties, and Performance AnalysisCode4
DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World KnowledgeCode3
Ovis-U1 Technical ReportCode3
ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image GenerationCode3
Machine Mental Imagery: Empower Multimodal Reasoning with Latent Visual TokensCode3
Highly Compressed Tokenizer Can Generate Without TrainingCode3
Ultra-High-Resolution Image Synthesis: Data, Method and EvaluationCode3
Nexus-Gen: A Unified Model for Image Understanding, Generation, and EditingCode3
PixelHacker: Image Inpainting with Structural and Semantic ConsistencyCode3
REPA-E: Unlocking VAE for End-to-End Tuning of Latent Diffusion TransformersCode3
GigaTok: Scaling Visual Tokenizers to 3 Billion Parameters for Autoregressive Image GenerationCode3
PixelFlow: Pixel-Space Generative Models with FlowCode3
DDT: Decoupled Diffusion TransformerCode3
GPT-ImgEval: A Comprehensive Benchmark for Diagnosing GPT4o in Image GenerationCode3
VARGPT-v1.1: Improve Visual Autoregressive Large Unified Model via Iterative Instruction Tuning and Reinforcement LearningCode3
AnimeGamer: Infinite Anime Life Simulation with Next Game State PredictionCode3
AI2Agent: An End-to-End Framework for Deploying AI Projects as Autonomous AgentsCode3
Optimal Stepsize for Diffusion SamplingCode3
Diffusion-4K: Ultra-High-Resolution Image Synthesis with Latent Diffusion ModelsCode3
Halton Scheduler For Masked Generative Image TransformerCode3
GoT: Unleashing Reasoning Capability of Multimodal Large Language Model for Visual Generation and EditingCode3
Robust Latent Matters: Boosting Image Generation with Sampling ErrorCode3
Kiss3DGen: Repurposing Image Diffusion Models for 3D Asset GenerationCode3
Attention Distillation: A Unified Approach to Visual Characteristics TransferCode3
Beyond Next-Token: Next-X Prediction for Autoregressive Visual GenerationCode3
ART: Anonymous Region Transformer for Variable Multi-Layer Transparent Image GenerationCode3
DICEPTION: A Generalist Diffusion Model for Visual Perceptual TasksCode3
Personalized Image Generation with Deep Generative Models: A Decade SurveyCode3
LLMs can see and hear without any trainingCode3
One-Prompt-One-Story: Free-Lunch Consistent Text-to-Image Generation Using a Single PromptCode3
VARGPT: Unified Understanding and Generation in a Visual Autoregressive Multimodal Large Language ModelCode3
3DIS-FLUX: simple and efficient multi-instance generation with DiT renderingCode3
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers UpCode3
Attentive Eraser: Unleashing Diffusion Model's Object Removal Potential via Self-Attention Redirection GuidanceCode3
SoftVQ-VAE: Efficient 1-Dimensional Continuous TokenizerCode3
TokenFlow: Unified Image Tokenizer for Multimodal Understanding and GenerationCode3
MuLan: Adapting Multilingual Diffusion Models for Hundreds of Languages with Negligible CostCode3
Kandinsky 3: Text-to-Image Synthesis for Multifunctional Generative FrameworkCode3
FiTv2: Scalable and Improved Flexible Vision Transformer for Diffusion ModelCode3
3DIS: Depth-Driven Decoupled Instance Synthesis for Text-to-Image GenerationCode3
CtrLoRA: An Extensible and Efficient Framework for Controllable Image GenerationCode3
SceneCraft: Layout-Guided 3D Scene GenerationCode3
Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image SynthesisCode3
AP-LDM: Attentive and Progressive Latent Diffusion Model for Training-Free High-Resolution Image GenerationCode3
ControlAR: Controllable Image Generation with Autoregressive ModelsCode3
Accelerating Auto-regressive Text-to-Image Generation with Training-free Speculative Jacobi DecodingCode3
ImageFolder: Autoregressive Image Generation with Folded TokensCode3
Simple and Fast Distillation of Diffusion ModelsCode3
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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