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 951975 of 6689 papers

TitleStatusHype
CACTI: A Framework for Scalable Multi-Task Multi-Scene Visual Imitation LearningCode1
Flow Contrastive Estimation of Energy-Based ModelsCode1
Accelerating Guided Diffusion Sampling with Splitting Numerical MethodsCode1
Cached Multi-Lora Composition for Multi-Concept Image GenerationCode1
FlexIT: Towards Flexible Semantic Image TranslationCode1
CLIP-Diffusion-LM: Apply Diffusion Model on Image CaptioningCode1
CLIP-Forge: Towards Zero-Shot Text-to-Shape GenerationCode1
CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIPCode1
C2N: Practical Generative Noise Modeling for Real-World DenoisingCode1
Anycost GANs for Interactive Image Synthesis and EditingCode1
FlexiFilm: Long Video Generation with Flexible ConditionsCode1
Clockwork Diffusion: Efficient Generation With Model-Step DistillationCode1
CLoG: Benchmarking Continual Learning of Image Generation ModelsCode1
Histo-fetch -- On-the-fly processing of gigapixel whole slide images simplifies and speeds neural network trainingCode1
Synthesizing Optical and SAR Imagery From Land Cover Maps and Auxiliary Raster DataCode1
ArtiFact: A Large-Scale Dataset with Artificial and Factual Images for Generalizable and Robust Synthetic Image DetectionCode1
Adv-Diffusion: Imperceptible Adversarial Face Identity Attack via Latent Diffusion ModelCode1
Cloud Removal in Satellite Images Using Spatiotemporal Generative NetworksCode1
HoughNet: Integrating near and long-range evidence for visual detectionCode1
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative ModelsCode1
FLAME Diffuser: Wildfire Image Synthesis using Mask Guided DiffusionCode1
CNN-generated images are surprisingly easy to spot... for nowCode1
Unsupervised Sketch-to-Photo SynthesisCode1
BS-LDM: Effective Bone Suppression in High-Resolution Chest X-Ray Images with Conditional Latent Diffusion ModelsCode1
One Image is Worth a Thousand Words: A Usability Preservable Text-Image Collaborative Erasing FrameworkCode1
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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