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 63516400 of 6689 papers

TitleStatusHype
High-Fidelity Image Compression with Score-based Generative Models0
High-Fidelity Image Generation With Fewer Labels0
High-Fidelity Image Synthesis from Pulmonary Nodule Lesion Maps using Semantic Diffusion Model0
The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models0
The power of pictures: using ML assisted image generation to engage the crowd in complex socioscientific problems0
TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts0
Highly accelerated MR parametric mapping by undersampling the k-space and reducing the contrast number simultaneously with deep learning0
AUTM Flow: Atomic Unrestricted Time Machine for Monotonic Normalizing Flows0
Highly Personalized Text Embedding for Image Manipulation by Stable Diffusion0
High Noise Scheduling is a Must0
High Precision Score-based Diffusion Models0
High Quality Diffusion Distillation on a Single GPU with Relative and Absolute Position Matching0
High-Quality Medical Image Generation from Free-hand Sketch0
High-resolution efficient image generation from WiFi CSI using a pretrained latent diffusion model0
ACE: Attentional Concept Erasure in Diffusion Models0
The Right Losses for the Right Gains: Improving the Semantic Consistency of Deep Text-to-Image Generation with Distribution-Sensitive Losses0
High-Resolution Image Synthesis via Next-Token Prediction0
Manifold Constraint Regularization for Remote Sensing Image Generation0
High-Resolution Mammogram Synthesis using Progressive Generative Adversarial Networks0
High-resolution medical image synthesis using progressively grown generative adversarial networks0
High Resolution Seismic Waveform Generation using Denoising Diffusion0
High Resolution Solar Image Generation using Generative Adversarial Networks0
High-Resolution UAV Image Generation for Sorghum Panicle Detection0
Thermal to Visible Image Synthesis under Atmospheric Turbulence0
Accurate Ground-Truth Depth Image Generation via Overfit Training of Point Cloud Registration using Local Frame Sets0
HiPA: Enabling One-Step Text-to-Image Diffusion Models via High-Frequency-Promoting Adaptation0
Thermoxels: a voxel-based method to generate simulation-ready 3D thermal models0
HiREN: Towards Higher Supervision Quality for Better Scene Text Image Super-Resolution0
HiScene: Creating Hierarchical 3D Scenes with Isometric View Generation0
The Role of Generative AI in Facilitating Social Interactions: A Scoping Review0
The Silent Prompt: Initial Noise as Implicit Guidance for Goal-Driven Image Generation0
The Spectral Bias of Polynomial Neural Networks0
HiWave: Training-Free High-Resolution Image Generation via Wavelet-Based Diffusion Sampling0
HMAR: Efficient Hierarchical Masked Auto-Regressive Image Generation0
Accurate Compression of Text-to-Image Diffusion Models via Vector Quantization0
HOIDiffusion: Generating Realistic 3D Hand-Object Interaction Data0
Holistic Evaluation for Interleaved Text-and-Image Generation0
The State of the Art when using GPUs in Devising Image Generation Methods Using Deep Learning0
The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimation0
How Animals Dance (When You're Not Looking)0
How do Minimum-Norm Shallow Denoisers Look in Function Space?0
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling0
How Generative Adversarial Networks and Their Variants Work: An Overview0
How Image Generation Helps Visible-to-Infrared Person Re-Identification?0
How Real Is Real? A Human Evaluation Framework for Unrestricted Adversarial Examples0
How Stable is Stable Diffusion under Recursive InPainting (RIP)?0
How to build a consistency model: Learning flow maps via self-distillation0
How to Construct Energy for Images? Denoising Autoencoder Can Be Energy Based Model0
How to Fill the Optimum Set? Population Gradient Descent with Harmless Diversity0
The Swiss Army Knife for Image-to-Image Translation: Multi-Task Diffusion Models0
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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