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 2701–2750 of 6689 papers

TitleStatusHype
Training-Free Safe Denoisers for Safe Use of Diffusion Models—0
CausalGeD: Blending Causality and Diffusion for Spatial Gene Expression Generation—0
CAT: Contrastive Adversarial Training for Evaluating the Robustness of Protective Perturbations in Latent Diffusion ModelsCode0
Magic 1-For-1: Generating One Minute Video Clips within One MinuteCode0
SketchFlex: Facilitating Spatial-Semantic Coherence in Text-to-Image Generation with Region-Based SketchesCode0
Optimizing Knowledge Distillation in Transformers: Enabling Multi-Head Attention without Alignment Barriers—0
FlexControl: Computation-Aware ControlNet with Differentiable Router for Text-to-Image GenerationCode0
SurGrID: Controllable Surgical Simulation via Scene Graph to Image Diffusion—0
A Survey of Representation Learning, Optimization Strategies, and Applications for Omnidirectional Vision—0
Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing—0
Outsourced diffusion sampling: Efficient posterior inference in latent spaces of generative models—0
CustomVideoX: 3D Reference Attention Driven Dynamic Adaptation for Zero-Shot Customized Video Diffusion Transformers—0
From Image to Video: An Empirical Study of Diffusion Representations—0
Diverse Image Generation with Diffusion Models and Cross Class Label Learning for Polyp ClassificationCode0
BF-GAN: Development of an AI-driven Bubbly Flow Image Generation Model Using Generative Adversarial NetworksCode0
Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment—0
Bridging Scales in Map Generation: A scale-aware cascaded generative mapping framework for seamless and consistent multi-scale cartographic representation—0
G2PDiffusion: Genotype-to-Phenotype Prediction with Diffusion Models—0
QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation—0
DICE: Distilling Classifier-Free Guidance into Text Embeddings—0
Decoder-Only LLMs are Better Controllers for Diffusion Models—0
Generative Adversarial Networks Bridging Art and Machine Intelligence—0
Towards Fair and Robust Face Parsing for Generative AI: A Multi-Objective Approach—0
Augmented Conditioning Is Enough For Effective Training Image Generation—0
FairT2I: Mitigating Social Bias in Text-to-Image Generation via Large Language Model-Assisted Detection and Attribute Rebalancing—0
TruePose: Human-Parsing-guided Attention Diffusion for Full-ID Preserving Pose Transfer—0
On Fairness of Unified Multimodal Large Language Model for Image Generation—0
Poisson Flow Joint Model for Multiphase contrast-enhanced CT—0
Masked Autoencoders Are Effective Tokenizers for Diffusion Models—0
When are Diffusion Priors Helpful in Sparse Reconstruction? A Study with Sparse-view CT—0
Layer Separation: Adjustable Joint Space Width Images Synthesis in Conventional Radiography—0
Diffusion Instruction Tuning—0
AAD-DCE: An Aggregated Multimodal Attention Mechanism for Early and Late Dynamic Contrast Enhanced Prostate MRI SynthesisCode0
Towards Consistent and Controllable Image Synthesis for Face Editing—0
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models—0
Unpaired Deblurring via Decoupled Diffusion Model—0
Texture Image Synthesis Using Spatial GAN Based on Vision Transformers—0
RealRAG: Retrieval-augmented Realistic Image Generation via Self-reflective Contrastive Learning—0
Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target GenerationCode0
CAT Pruning: Cluster-Aware Token Pruning For Text-to-Image Diffusion ModelsCode0
Video Latent Flow Matching: Optimal Polynomial Projections for Video Interpolation and Extrapolation—0
Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms—0
Distorting Embedding Space for Safety: A Defense Mechanism for Adversarially Robust Diffusion ModelsCode0
BCAT: A Block Causal Transformer for PDE Foundation Models for Fluid Dynamics—0
Ambient Denoising Diffusion Generative Adversarial Networks for Establishing Stochastic Object Models from Noisy Image Data—0
REG: Rectified Gradient Guidance for Conditional Diffusion Models—0
Diffusion Autoencoders are Scalable Image Tokenizers—0
Segmentation-Aware Generative Reinforcement Network (GRN) for Tissue Layer Segmentation in 3-D Ultrasound Images for Chronic Low-back Pain (cLBP) AssessmentCode0
Generative AI for Vision: A Comprehensive Study of Frameworks and Applications—0
DebiasPI: Inference-time Debiasing by Prompt Iteration of a Text-to-Image Generative Model—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