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 3651–3700 of 6689 papers

TitleStatusHype
StableMaterials: Enhancing Diversity in Material Generation via Semi-Supervised Learning—0
FontStudio: Shape-Adaptive Diffusion Model for Coherent and Consistent Font Effect Generation—0
What If We Recaption Billions of Web Images with LLaMA-3?—0
DiTFastAttn: Attention Compression for Diffusion Transformer Models—0
Words Worth a Thousand Pictures: Measuring and Understanding Perceptual Variability in Text-to-Image Generation—0
WMAdapter: Adding WaterMark Control to Latent Diffusion Models—0
Understanding and Mitigating Compositional Issues in Text-to-Image Generative ModelsCode0
Diffusion Soup: Model Merging for Text-to-Image Diffusion Models—0
Ctrl-X: Controlling Structure and Appearance for Text-To-Image Generation Without Guidance—0
Beware of Aliases -- Signal Preservation is Crucial for Robust Image Restoration—0
Understanding Visual Concepts Across ModelsCode0
Progress Towards Decoding Visual Imagery via fNIRS—0
Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?—0
Eye-for-an-eye: Appearance Transfer with Semantic Correspondence in Diffusion Models—0
Instant 3D Human Avatar Generation using Image Diffusion Models—0
The Effect of Training Dataset Size on Discriminative and Diffusion-Based Speech Enhancement Systems—0
Can Prompt Modifiers Control Bias? A Comparative Analysis of Text-to-Image Generative Models—0
TIGeR: Unifying Text-to-Image Generation and Retrieval with Large Multimodal Models—0
OmniControlNet: Dual-stage Integration for Conditional Image Generation—0
Regularized Training with Generated Datasets for Name-Only Transfer of Vision-Language ModelsCode0
Rapid Review of Generative AI in Smart Medical Applications—0
GANetic Loss for Generative Adversarial Networks with a Focus on Medical ApplicationsCode0
AttnDreamBooth: Towards Text-Aligned Personalized Text-to-Image Generation—0
Optimal Eye Surgeon: Finding Image Priors through Sparse Generators at InitializationCode0
PQPP: A Joint Benchmark for Text-to-Image Prompt and Query Performance PredictionCode0
Coherent Zero-Shot Visual Instruction Generation—0
BitsFusion: 1.99 bits Weight Quantization of Diffusion Model—0
Diffusion-based image inpainting with internal learningCode0
ReDistill: Residual Encoded Distillation for Peak Memory Reduction—0
DiffuSyn Bench: Evaluating Vision-Language Models on Real-World Complexities with Diffusion-Generated Synthetic Benchmarks—0
Understanding the Limitations of Diffusion Concept Algebra Through Food—0
Inv-Adapter: ID Customization Generation via Image Inversion and Lightweight Adapter—0
Enhancing Traffic Sign Recognition with Tailored Data Augmentation: Addressing Class Imbalance and Instance Scarcity—0
Tackling Copyright Issues in AI Image Generation Through Originality Estimation and GenericizationCode0
Analyzing the Feature Extractor Networks for Face Image SynthesisCode0
The Crystal Ball Hypothesis in diffusion models: Anticipating object positions from initial noise—0
Enhance Image-to-Image Generation with LLaVA-generated Prompts—0
Plug-and-Play Diffusion Distillation—0
I4VGen: Image as Free Stepping Stone for Text-to-Video Generation—0
It's a Feature, Not a Bug: Measuring Creative Fluidity in Image Generators—0
Differentially Private Fine-Tuning of Diffusion Models—0
ATTIQA: Generalizable Image Quality Feature Extractor using Attribute-aware Pretraining—0
Δ-DiT: A Training-Free Acceleration Method Tailored for Diffusion TransformersCode0
Layout Agnostic Scene Text Image Synthesis with Diffusion Models—0
Anomaly Anything: Promptable Unseen Visual Anomaly Generation—0
Text-guided Controllable Mesh Refinement for Interactive 3D Modeling—0
fruit-SALAD: A Style Aligned Artwork Dataset to reveal similarity perception in image embeddingsCode0
pOps: Photo-Inspired Diffusion Operators—0
Dimba: Transformer-Mamba Diffusion Models—0
ParallelEdits: Efficient Multi-object Image Editing—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