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 45514575 of 6689 papers

TitleStatusHype
Temporally Adjustable Longitudinal Fluid-Attenuated Inversion Recovery MRI Estimation / Synthesis for Multiple Sclerosis0
Lightweight Long-Range Generative Adversarial Networks0
Foundations and Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questions0
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified FlowCode3
AI Illustrator: Translating Raw Descriptions into Images by Prompt-based Cross-Modal GenerationCode1
A Scene-Text Synthesis Engine Achieved Through Learning from Decomposed Real-World DataCode1
MMV_Im2Im: An Open Source Microscopy Machine Vision Toolbox for Image-to-Image TransformationCode1
Semantic Image Synthesis with Semantically Coupled VQ-Model0
Synthesizing Photorealistic Virtual Humans Through Cross-modal Disentanglement0
DSE-GAN: Dynamic Semantic Evolution Generative Adversarial Network for Text-to-Image Generation0
SIAN: Style-Guided Instance-Adaptive Normalization for Multi-Organ Histopathology Image Synthesis0
Diffusion Models: A Comprehensive Survey of Methods and ApplicationsCode4
Deep Unrolled Low-Rank Tensor Completion for High Dynamic Range ImagingCode1
Frido: Feature Pyramid Diffusion for Complex Scene Image SynthesisCode1
LogicRank: Logic Induced Reranking for Generative Text-to-Image Systems0
Training and Tuning Generative Neural Radiance Fields for Attribute-Conditional 3D-Aware Face GenerationCode1
Adaptively-Realistic Image Generation from Stroke and Sketch with Diffusion Model0
Deformation equivariant cross-modality image synthesis with paired non-aligned training dataCode0
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven GenerationCode5
Understanding Diffusion Models: A Unified Perspective0
Discovering Transferable Forensic Features for CNN-generated Images DetectionCode1
Unsupervised Structure-Consistent Image-to-Image Translation0
DepthFake: a depth-based strategy for detecting Deepfake videos0
The Value of AI Guidance in Human Examination of Synthetically-Generated Faces0
FurryGAN: High Quality Foreground-aware Image Synthesis0
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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