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 1151–1200 of 6689 papers

TitleStatusHype
EMOv2: Pushing 5M Vision Model FrontierCode2
Proactive Agents for Multi-Turn Text-to-Image Generation Under UncertaintyCode2
Precise, Fast, and Low-cost Concept Erasure in Value Space: Orthogonal Complement MattersCode1
ContRail: A Framework for Realistic Railway Image Synthesis using ControlNet—0
Efficiency Meets Fidelity: A Novel Quantization Framework for Stable Diffusion—0
ILLUME: Illuminating Your LLMs to See, Draw, and Self-Enhance—0
Open-Source Acceleration of Stable-Diffusion.cpp Deployable on All DevicesCode0
Nested Diffusion Models Using Hierarchical Latent Priors—0
BudgetFusion: Perceptually-Guided Adaptive Diffusion Models—0
Self-Guidance: Boosting Flow and Diffusion Generation on Their Own—0
FlexDiT: Dynamic Token Density Control for Diffusion TransformerCode1
SILMM: Self-Improving Large Multimodal Models for Compositional Text-to-Image Generation—0
Language-Guided Image Tokenization for Generation—0
BiDM: Pushing the Limit of Quantization for Diffusion ModelsCode1
GraPE: A Generate-Plan-Edit Framework for Compositional T2I Synthesis—0
CSG: A Context-Semantic Guided Diffusion Approach in De Novo Musculoskeletal Ultrasound Image Generation—0
Not Just Text: Uncovering Vision Modality Typographic Threats in Image Generation Models—0
A Tiered GAN Approach for Monet-Style Image Generation—0
The Silent Prompt: Initial Noise as Implicit Guidance for Goal-Driven Image Generation—0
LoRA.rar: Learning to Merge LoRAs via Hypernetworks for Subject-Style Conditioned Image GenerationCode1
Noise Matters: Diffusion Model-based Urban Mobility Generation with Collaborative Noise Priors—0
Continuous Video Process: Modeling Videos as Continuous Multi-Dimensional Processes for Video Prediction—0
AnyDressing: Customizable Multi-Garment Virtual Dressing via Latent Diffusion Models—0
T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts—0
Infinity: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image SynthesisCode9
One Communication Round is All It Needs for Federated Fine-Tuning Foundation Models—0
BodyMetric: Evaluating the Realism of Human Bodies in Text-to-Image Generation—0
LayerFusion: Harmonized Multi-Layer Text-to-Image Generation with Generative Priors—0
Local Curvature Smoothing with Stein's Identity for Efficient Score Matching—0
ZipAR: Accelerating Auto-regressive Image Generation through Spatial LocalityCode2
The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation—0
A Framework For Image Synthesis Using Supervised Contrastive Learning—0
Structure-Aware Stylized Image Synthesis for Robust Medical Image SegmentationCode0
Multi-Subject Image Synthesis as a Generative Prior for Single-Subject PET Image Reconstruction—0
A Noise is Worth Diffusion Guidance—0
CreatiLayout: Siamese Multimodal Diffusion Transformer for Creative Layout-to-Image Generation—0
Safeguarding Text-to-Image Generation via Inference-Time Prompt-Noise OptimizationCode0
Seamless Optical Cloud Computing across Edge-Metro Network for Generative AI—0
MRGen: Diffusion-based Controllable Data Engine for MRI Segmentation towards Unannotated ModalitiesCode1
Geometry-guided Cross-view Diffusion for One-to-many Cross-view Image Synthesis—0
Partially Conditioned Patch Parallelism for Accelerated Diffusion Model Inference—0
PatchDPO: Patch-level DPO for Finetuning-free Personalized Image GenerationCode1
Appearance Matching Adapter for Exemplar-based Semantic Image Synthesis—0
Implicit Priors Editing in Stable Diffusion via Targeted Token Adjustment—0
DIVE: Taming DINO for Subject-Driven Video Editing—0
Multi-view Image Diffusion via Coordinate Noise and Fourier Attention—0
Towards Understanding and Quantifying Uncertainty for Text-to-Image Generation—0
Is JPEG AI going to change image forensics?Code1
DynamicControl: Adaptive Condition Selection for Improved Text-to-Image Generation—0
Generalized Diffusion Model with Adjusted Offset Noise—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