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 151175 of 6689 papers

TitleStatusHype
Graph Flow Matching: Enhancing Image Generation with Neighbor-Aware Flow Fields0
Interpreting Large Text-to-Image Diffusion Models with Dictionary LearningCode0
ReasonGen-R1: CoT for Autoregressive Image generation models through SFT and RLCode2
Multi-Group Proportional Representation for Text-to-Image Models0
VisualSphinx: Large-Scale Synthetic Vision Logic Puzzles for RL0
Muddit: Liberating Generation Beyond Text-to-Image with a Unified Discrete Diffusion ModelCode2
LoRAShop: Training-Free Multi-Concept Image Generation and Editing with Rectified Flow Transformers0
R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generation0
VITON-DRR: Details Retention Virtual Try-on via Non-rigid RegistrationCode0
Inference-time Scaling of Diffusion Models through Classical Search0
RSFAKE-1M: A Large-Scale Dataset for Detecting Diffusion-Generated Remote Sensing Forgeries0
Implicit Inversion turns CLIP into a DecoderCode0
How Animals Dance (When You're Not Looking)0
Image Aesthetic Reasoning: A New Benchmark for Medical Image Screening with MLLMs0
Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis0
Diffusion Sampling Path Tells More: An Efficient Plug-and-Play Strategy for Sample FilteringCode0
Cross-modal RAG: Sub-dimensional Retrieval-Augmented Text-to-Image GenerationCode0
Rhetorical Text-to-Image Generation via Two-layer Diffusion Policy Optimization0
Principled Out-of-Distribution Generalization via Simplicity0
HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion TransformerCode7
Uni-Instruct: One-step Diffusion Model through Unified Diffusion Divergence Instruction0
DetailFlow: 1D Coarse-to-Fine Autoregressive Image Generation via Next-Detail PredictionCode2
Unveiling Impact of Frequency Components on Membership Inference Attacks for Diffusion Models0
Creativity in LLM-based Multi-Agent Systems: A Survey0
ImgEdit: A Unified Image Editing Dataset and BenchmarkCode4
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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