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 18511875 of 6689 papers

TitleStatusHype
Step Saver: Predicting Minimum Denoising Steps for Diffusion Model Image Generation0
SkyDiffusion: Ground-to-Aerial Image Synthesis with Diffusion Models and BEV Paradigm0
A Novel Evaluation Framework for Image2Text Generation0
VAR-CLIP: Text-to-Image Generator with Visual Auto-Regressive ModelingCode2
EIUP: A Training-Free Approach to Erase Non-Compliant Concepts Conditioned on Implicit Unsafe Prompts0
FBSDiff: Plug-and-Play Frequency Band Substitution of Diffusion Features for Highly Controllable Text-Driven Image TranslationCode1
A Simple Background Augmentation Method for Object Detection with Diffusion Model0
Few-shot Defect Image Generation based on Consistency ModelingCode1
Temporal Evolution of Knee Osteoarthritis: A Diffusion-based Morphing Model for X-ray Medical Image Synthesis0
Smoothed Energy Guidance: Guiding Diffusion Models with Reduced Energy Curvature of AttentionCode2
Synthetic dual image generation for reduction of labeling efforts in semantic segmentation of micrographs with a customized metric function0
Fuzz-Testing Meets LLM-Based Agents: An Automated and Efficient Framework for Jailbreaking Text-To-Image Generation ModelsCode1
A new approach for encoding code and assisting code understanding0
Towards Reliable Advertising Image Generation Using Human FeedbackCode2
Detecting, Explaining, and Mitigating Memorization in Diffusion ModelsCode2
Deformable 3D Shape Diffusion Model0
Fine-gained Zero-shot Video Sampling0
WAS: Dataset and Methods for Artistic Text SegmentationCode1
Vulnerabilities in AI-generated Image Detection: The Challenge of Adversarial Attacks0
Autonomous Improvement of Instruction Following Skills via Foundation ModelsCode2
Enhancing Quantitative Image Synthesis through Pretraining and Resolution Scaling for Bone Mineral Density Estimation from a Plain X-ray ImageCode0
Retinex-Diffusion: On Controlling Illumination Conditions in Diffusion Models via Retinex Theory0
MaskInversion: Localized Embeddings via Optimization of Explainability Maps0
Reproducibility Study of "ITI-GEN: Inclusive Text-to-Image Generation"Code0
MVPbev: Multi-view Perspective Image Generation from BEV with Test-time Controllability and GeneralizabilityCode1
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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