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

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Showing 5026–5050 of 6689 papers

TitleStatusHype
Physics-Inspired Generative Models in Medical Imaging: A Review—0
Physics Validation of Novel Convolutional 2D Architectures for Speeding Up High Energy Physics Simulations—0
PI3D: Efficient Text-to-3D Generation with Pseudo-Image Diffusion—0
Analyzing CLIP's Performance Limitations in Multi-Object Scenarios: A Controlled High-Resolution Study—0
Picture that Sketch: Photorealistic Image Generation from Abstract Sketches—0
PIDiff: Image Customization for Personalized Identities with Diffusion Models—0
Analyzing and Improving Model Collapse in Rectified Flow Models—0
3D-Aware Indoor Scene Synthesis with Depth Priors—0
Pipeline Enabling Zero-shot Classification for Bangla Handwritten Grapheme—0
Pipeline Generative Adversarial Networks for Facial Images Generation with Multiple Attributes—0
Unifying Generation and Compression: Ultra-low bitrate Image Coding Via Multi-stage Transformer—0
Pisces: An Auto-regressive Foundation Model for Image Understanding and Generation—0
WikiArt Emotions: An Annotated Dataset of Emotions Evoked by Art—0
PIV/BOS Synthetic Image Generation in Variable Density Environments for Error Analysis and Experiment Design—0
Analytical Interpretation of Latent Codes in InfoGAN with SAR Images—0
UniGen: Enhanced Training & Test-Time Strategies for Unified Multimodal Understanding and Generation—0
Analysing Diffusion Segmentation for Medical Images—0
An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection—0
"An Adapt-or-Die Type of Situation": Perception, Adoption, and Use of Text-To-Image-Generation AI by Game Industry Professionals—0
Adaptive Gradient Regularization: A Faster and Generalizable Optimization Technique for Deep Neural Networks—0
UniGlyph: Unified Segmentation-Conditioned Diffusion for Precise Visual Text Synthesis—0
PixelCNN Models with Auxiliary Variables for Natural Image Modeling—0
An Acceleration Framework for High Resolution Image Synthesis—0
3D-aware Image Generation using 2D Diffusion Models—0
A Mutual Information Perspective on Multiple Latent Variable Generative Models for Positive View Generation—0
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All datasetsImageNet 256x256CIFAR-10ImageNet 64x64ImageNet 512x512FFHQ 256 x 256CelebA 64x64ImageNet 32x32LSUN Bedroom 256 x 256STL-10LSUN Churches 256 x 256ImageNet 128x128FFHQ 1024 x 1024

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Improved DDPMFID12.3—Unverified
2ADMFID11.84—Unverified
3BigGAN-deepFID8.1—Unverified
4Polarity-BigGANFID6.82—Unverified
5VQGAN+Transformer (k=mixed, p=1.0, a=0.005)FID6.59—Unverified
6MaskGITFID6.18—Unverified
7VQGAN+Transformer (k=600, p=1.0, a=0.05)FID5.2—Unverified
8CDMFID4.88—Unverified
9ADM-GFID4.59—Unverified
10RINFID4.51—Unverified
#ModelMetricClaimedVerifiedStatus
1PresGANFID52.2—Unverified
2RESFLOWFID48.29—Unverified
3Residual FlowFID46.37—Unverified
4GLF+perceptual loss (ours)FID44.6—Unverified
5ProdPoly no activation functionsFID40.45—Unverified
6ProdPoly no activation functionsFID36.77—Unverified
7ACGANFID35.47—Unverified
8DenseFlow-74-10FID34.9—Unverified
9NVAE w/ flowFID32.53—Unverified
10QSNGANFID31.97—Unverified
#ModelMetricClaimedVerifiedStatus
1GLIDE + CLSFID30.87—Unverified
2GLIDE + CLIPFID30.46—Unverified
3GLIDE + CLS-FREEFID29.22—Unverified
4GLIDE + CLIP + CLS + CLS-FREEFID29.18—Unverified
5PGMGANFID21.73—Unverified
6CLR-GANFID20.27—Unverified
7FMFID14.45—Unverified
8CT (Direct Generation, NFE=1)FID13—Unverified
9CT (Direct Generation, NFE=2)FID11.1—Unverified
10GLIDE +CLSKID7.95—Unverified