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 25262550 of 6689 papers

TitleStatusHype
Diversity-aware Channel Pruning for StyleGAN CompressionCode1
TiBiX: Leveraging Temporal Information for Bidirectional X-ray and Report GenerationCode0
DetDiffusion: Synergizing Generative and Perceptive Models for Enhanced Data Generation and Perception0
BlendScape: Enabling End-User Customization of Video-Conferencing Environments through Generative AI0
IIDM: Image-to-Image Diffusion Model for Semantic Image SynthesisCode0
Towards Learning Contrast Kinetics with Multi-Condition Latent Diffusion ModelsCode1
ReGround: Improving Textual and Spatial Grounding at No CostCode0
IDAdapter: Learning Mixed Features for Tuning-Free Personalization of Text-to-Image Models0
AGFSync: Leveraging AI-Generated Feedback for Preference Optimization in Text-to-Image Generation0
Enhancing Fingerprint Image Synthesis with GANs, Diffusion Models, and Style Transfer Techniques0
S2DM: Sector-Shaped Diffusion Models for Video Generation0
Deepfake Detection without Deepfakes: Generalization via Synthetic Frequency Patterns InjectionCode0
Ultra-High-Resolution Image Synthesis with Pyramid Diffusion Model0
Controllable Face Synthesis with Semantic Latent Diffusion ModelsCode1
Tuning-Free Image Customization with Image and Text GuidanceCode2
Segment Anything for comprehensive analysis of grapevine cluster architecture and berry properties0
You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANsCode2
FouriScale: A Frequency Perspective on Training-Free High-Resolution Image SynthesisCode2
Generative Enhancement for 3D Medical ImagesCode2
Total Disentanglement of Font Images into Style and Character Class Features0
Enhancing GAN Performance through Neural Architecture Search and Tensor DecompositionCode0
Synthetic Image Generation in Cyber Influence Operations: An Emergent Threat?0
ThermoNeRF: Joint RGB and Thermal Novel View Synthesis for Building Facades using Multimodal Neural Radiance FieldsCode2
IDF-CR: Iterative Diffusion Process for Divide-and-Conquer Cloud Removal in Remote-sensing ImagesCode1
LayerDiff: Exploring Text-guided Multi-layered Composable Image Synthesis via Layer-Collaborative Diffusion Model0
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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