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 34263450 of 6689 papers

TitleStatusHype
Mutual Information Maximizing Quantum Generative Adversarial Network and Its Applications in Finance0
Accelerating Markov Chain Monte Carlo sampling with diffusion modelsCode1
StyleAdapter: A Unified Stylized Image Generation Model0
Relay Diffusion: Unifying diffusion process across resolutions for image synthesisCode2
Exploring Limits of Diffusion-Synthetic Training with Weakly Supervised Semantic Segmentation0
RSDiff: Remote Sensing Image Generation from Text Using Diffusion Model0
Diffusion Models with Deterministic Normalizing Flow PriorsCode0
Constrained CycleGAN for Effective Generation of Ultrasound Sector Images of Improved Spatial ResolutionCode0
RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model0
Bridge Diffusion Model: bridge non-English language-native text-to-image diffusion model with English communities0
Diffusion Model with Clustering-based Conditioning for Food Image Generation0
VideoGen: A Reference-Guided Latent Diffusion Approach for High Definition Text-to-Video Generation0
PathLDM: Text conditioned Latent Diffusion Model for HistopathologyCode1
DiffuGen: Adaptable Approach for Generating Labeled Image Datasets using Stable Diffusion ModelsCode1
Iterative Multi-granular Image Editing using Diffusion Models0
Unsupervised evaluation of GAN sample quality: Introducing the TTJac Score0
Towards High-Fidelity Text-Guided 3D Face Generation and Manipulation Using only Images0
Detecting Out-of-Context Image-Caption Pairs in News: A Counter-Intuitive MethodCode0
Diffusion Models for Interferometric Satellite Aperture RadarCode1
Generate Your Own Scotland: Satellite Image Generation Conditioned on MapsCode1
Any-Size-Diffusion: Toward Efficient Text-Driven Synthesis for Any-Size HD Images0
Improving Few-shot Image Generation by Structural Discrimination and Textural ModulationCode1
Semantic Image Synthesis via Class-Adaptive Cross-AttentionCode0
Intriguing Properties of Diffusion Models: An Empirical Study of the Natural Attack Capability in Text-to-Image Generative Models0
Elucidating the Exposure Bias in Diffusion ModelsCode1
Show:102550
← PrevPage 138 of 268Next →

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