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 9761000 of 6689 papers

TitleStatusHype
Contrasting Intra-Modal and Ranking Cross-Modal Hard Negatives to Enhance Visio-Linguistic Compositional UnderstandingCode1
C2N: Practical Generative Noise Modeling for Real-World DenoisingCode1
IDF-CR: Iterative Diffusion Process for Divide-and-Conquer Cloud Removal in Remote-sensing ImagesCode1
Anycost GANs for Interactive Image Synthesis and EditingCode1
IGUANe: a 3D generalizable CycleGAN for multicenter harmonization of brain MR imagesCode1
Continuous Speculative Decoding for Autoregressive Image GenerationCode1
FooDI-ML: a large multi-language dataset of food, drinks and groceries images and descriptionsCode1
Synthesizing Optical and SAR Imagery From Land Cover Maps and Auxiliary Raster DataCode1
ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image SynthesisCode1
AdvI2I: Adversarial Image Attack on Image-to-Image Diffusion modelsCode1
Image Captions are Natural Prompts for Text-to-Image ModelsCode1
Accelerating Parallel Sampling of Diffusion ModelsCode1
Adv-Diffusion: Imperceptible Adversarial Face Identity Attack via Latent Diffusion ModelCode1
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
Contrastive Feature Loss for Image PredictionCode1
CoLa-Diff: Conditional Latent Diffusion Model for Multi-Modal MRI SynthesisCode1
A Scene-Text Synthesis Engine Achieved Through Learning from Decomposed Real-World DataCode1
2D medical image synthesis using transformer-based denoising diffusion probabilistic modelCode1
BS-Diff: Effective Bone Suppression Using Conditional Diffusion Models from Chest X-Ray ImagesCode1
Brush Your Text: Synthesize Any Scene Text on Images via Diffusion ModelCode1
AntifakePrompt: Prompt-Tuned Vision-Language Models are Fake Image DetectorsCode1
Accelerating Score-based Generative Models with Preconditioned Diffusion SamplingCode1
Flow Contrastive Estimation of Energy-Based ModelsCode1
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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