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 23762400 of 6689 papers

TitleStatusHype
DiffPAD: Denoising Diffusion-based Adversarial Patch DecontaminationCode0
Multimodal Latent Language Modeling with Next-Token DiffusionCode0
HSRMamba: Efficient Wavelet Stripe State Space Model for Hyperspectral Image Super-ResolutionCode0
Multi-Objective Quality-Diversity in Unstructured and Unbounded SpacesCode0
Multi-modal Generation via Cross-Modal In-Context LearningCode0
Multimodal Benchmarking and Recommendation of Text-to-Image Generation ModelsCode0
Adversarial symmetric GANs: bridging adversarial samples and adversarial networksCode0
Multilingual Text-to-Image Generation Magnifies Gender Stereotypes and Prompt Engineering May Not Help YouCode0
Multi-Class Multi-Instance Count Conditioned Adversarial Image GenerationCode0
MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image GenerationCode0
Breast Cancer Immunohistochemical Image Generation: a Benchmark Dataset and Challenge ReviewCode0
Multi class activity classification in videos using Motion History Image generationCode0
Multi-Granularity Denoising and Bidirectional Alignment for Weakly Supervised Semantic SegmentationCode0
Multi-View Image-to-Image Translation Supervised by 3D PoseCode0
Pre-trained Perceptual Features Improve Differentially Private Image GenerationCode0
BSD-GAN: Branched Generative Adversarial Network for Scale-Disentangled Representation Learning and Image SynthesisCode0
Mukh-Oboyob: Stable Diffusion and BanglaBERT enhanced Bangla Text-to-Face SynthesisCode0
MRI Reconstruction Using Deep Energy-Based ModelCode0
MSG-GAN: Multi-Scale Gradients for Generative Adversarial NetworksCode0
Motion Transfer-Driven intra-class data augmentation for Finger Vein RecognitionCode0
MotionCom: Automatic and Motion-Aware Image Composition with LLM and Video Diffusion PriorCode0
MPG: A Multi-ingredient Pizza Image Generator with Conditional StyleGANsCode0
More comprehensive facial inversion for more effective expression recognitionCode0
More Expressive Attention with Negative WeightsCode0
MontageGAN: Generation and Assembly of Multiple Components by GANsCode0
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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