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 1901–1950 of 6689 papers

TitleStatusHype
GreenStableYolo: Optimizing Inference Time and Image Quality of Text-to-Image GenerationCode0
Latent Pollution Model: The Hidden Carbon Footprint in 3D Image Synthesis—0
CoCoG-2: Controllable generation of visual stimuli for understanding human concept representationCode0
Are handcrafted filters helpful for attributing AI-generated images?—0
Thinking Racial Bias in Fair Forgery Detection: Models, Datasets and EvaluationsCode1
Panoptic Segmentation of Mammograms with Text-To-Image Diffusion Model—0
Time Series Generative Learning with Application to Brain Imaging Analysis—0
Controllable and Efficient Multi-Class Pathology Nuclei Data Augmentation using Text-Conditioned Diffusion Models—0
SUSTechGAN: Image Generation for Object Detection in Adverse Conditions of Autonomous DrivingCode0
Image Inpainting Models are Effective Tools for Instruction-guided Image Editing—0
Training-free Composite Scene Generation for Layout-to-Image SynthesisCode1
Safe-SD: Safe and Traceable Stable Diffusion with Text Prompt Trigger for Invisible Generative Watermarking—0
URCDM: Ultra-Resolution Image Synthesis in HistopathologyCode0
GeoGuide: Geometric guidance of diffusion modelsCode0
Promptable Counterfactual Diffusion Model for Unified Brain Tumor Segmentation and Generation with MRIsCode0
Latent Diffusion for Medical Image Segmentation: End to end learning for fast sampling and accuracyCode1
From Principles to Practices: Lessons Learned from Applying Partnership on AI's (PAI) Synthetic Media Framework to 11 Use Cases—0
The Fabrication of Reality and Fantasy: Scene Generation with LLM-Assisted Prompt Interpretation—0
I2AM: Interpreting Image-to-Image Latent Diffusion Models via Attribution Maps—0
Towards Understanding Unsafe Video GenerationCode0
Voltage-Controlled Magnetoelectric Devices for Neuromorphic Diffusion Process—0
Zero-shot Text-guided Infinite Image Synthesis with LLM guidance—0
IMAGDressing-v1: Customizable Virtual DressingCode5
Scaling Diffusion Transformers to 16 Billion ParametersCode3
Flatfish Disease Detection Based on Part Segmentation Approach and Disease Image Generation—0
Mask-guided cross-image attention for zero-shot in-silico histopathologic image generation with a diffusion model—0
Subject-driven Text-to-Image Generation via Preference-based Reinforcement LearningCode0
Beta Sampling is All You Need: Efficient Image Generation Strategy for Diffusion Models using Stepwise Spectral Analysis—0
How Control Information Influences Multilingual Text Image Generation and Editing?Code0
Efficient Training with Denoised Neural Weights—0
DiNO-Diffusion. Scaling Medical Diffusion via Self-Supervised Pre-Training—0
Zero-Shot Adaptation for Approximate Posterior Sampling of Diffusion Models in Inverse ProblemsCode0
Optical Diffusion Models for Image Generation—0
Domain Generalization for 6D Pose Estimation Through NeRF-based Image Synthesis—0
AccDiffusion: An Accurate Method for Higher-Resolution Image GenerationCode2
Addressing Image Hallucination in Text-to-Image Generation through Factual Image Retrieval—0
InsertDiffusion: Identity Preserving Visualization of Objects through a Training-Free Diffusion ArchitectureCode1
DataDream: Few-shot Guided Dataset GenerationCode2
OPa-Ma: Text Guided Mamba for 360-degree Image Out-painting—0
Physics-Inspired Generative Models in Medical Imaging: A Review—0
A Survey of Defenses against AI-generated Visual Media: Detection, Disruption, and Authentication—0
Restore-RWKV: Efficient and Effective Medical Image Restoration with RWKVCode2
ContextualStory: Consistent Visual Storytelling with Spatially-Enhanced and Storyline ContextCode0
Layout-and-Retouch: A Dual-stage Framework for Improving Diversity in Personalized Image Generation—0
PSC: Posterior Sampling-Based CompressionCode1
Surgical Text-to-Image Generation—0
PID: Physics-Informed Diffusion Model for Infrared Image GenerationCode2
Region Attention Transformer for Medical Image RestorationCode1
LAPT: Label-driven Automated Prompt Tuning for OOD Detection with Vision-Language ModelsCode1
FairyLandAI: Personalized Fairy Tales utilizing ChatGPT and DALLE-3—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