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 5201–5250 of 6689 papers

TitleStatusHype
Denoising Task Difficulty-based Curriculum for Training Diffusion Models—0
Denoising with a Joint-Embedding Predictive Architecture—0
Dense-Face: Personalized Face Generation Model via Dense Annotation Prediction—0
A Data Augmentation Pipeline to Generate Synthetic Labeled Datasets of 3D Echocardiography Images using a GAN—0
DensePANet: An improved generative adversarial network for photoacoustic tomography image reconstruction from sparse data—0
Style and Content Disentanglement in Generative Adversarial Networks—0
Cali-Sketch: Stroke Calibration and Completion for High-Quality Face Image Generation from Human-Like Sketches—0
Unpriortized Autoencoder For Image Generation—0
Style and Pose Control for Image Synthesis of Humans from a Single Monocular View—0
Dependability Evaluation of Stable Diffusion with Soft Errors on the Model Parameters—0
DepthART: Monocular Depth Estimation as Autoregressive Refinement Task—0
DepthFake: a depth-based strategy for detecting Deepfake videos—0
Depth-SIMS: Semi-Parametric Image and Depth Synthesis—0
Depth Structure Preserving Scene Image Generation—0
DepthwiseGANs: Fast Training Generative Adversarial Networks for Realistic Image Synthesis—0
StyleAR: Customizing Multimodal Autoregressive Model for Style-Aligned Text-to-Image Generation—0
Style-based Encoder Pre-training for Multi-modal Image Synthesis—0
DesignDiffusion: High-Quality Text-to-Design Image Generation with Diffusion Models—0
Calibrated Vehicle Paint Signatures for Simulating Hyperspectral Imagery—0
Designing a Conditional Prior Distribution for Flow-Based Generative Models—0
Designing Counterfactual Generators using Deep Model Inversion—0
Designing GANs: A Likelihood Ratio Approach—0
Detailed Human-Centric Text Description-Driven Large Scene Synthesis—0
CA-GAN: Weakly Supervised Color Aware GAN for Controllable Makeup Transfer—0
DetDiffusion: Synergizing Generative and Perceptive Models for Enhanced Data Generation and Perception—0
Detect-and-Guide: Self-regulation of Diffusion Models for Safe Text-to-Image Generation via Guideline Token Optimization—0
Detecting Dataset Abuse in Fine-Tuning Stable Diffusion Models for Text-to-Image Synthesis—0
CAGAN: Text-To-Image Generation with Combined Attention GANs—0
Detecting Face Synthesis Using a Concealed Fusion Model—0
Detecting High-Quality GAN-Generated Face Images using Neural Networks—0
You Only Scan Once: Efficient Multi-dimension Sequential Modeling with LightNet—0
Detecting Malicious Concepts Without Image Generation in AIGC—0
Perceptual underwater image enhancement with deep learning and physical priors—0
Style-Content Disentanglement in Language-Image Pretraining Representations for Zero-Shot Sketch-to-Image Synthesis—0
Adaptive Non-Uniform Timestep Sampling for Accelerating Diffusion Model Training—0
Development of an Unpaired Deep Neural Network for Synthesizing X-ray Fluoroscopic Images from Digitally Reconstructed Tomography in Image Guided Radiotherapy—0
Devil is in the Detail: Towards Injecting Fine Details of Image Prompt in Image Generation via Conflict-free Guidance and Stratified Attention—0
CAFLOW: Conditional Autoregressive Flows—0
D-Feat Occlusions: Diffusion Features for Robustness to Partial Visual Occlusions in Object Recognition—0
Style-Extracting Diffusion Models for Semi-Supervised Histopathology Segmentation—0
Visible-Infrared Person Re-Identification via Patch-Mixed Cross-Modality Learning—0
VisioBlend: Sketch and Stroke-Guided Denoising Diffusion Probabilistic Model for Realistic Image Generation—0
Adaptive Non-Uniform Timestep Sampling for Diffusion Model Training—0
CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling—0
DICE: Discrete Inversion Enabling Controllable Editing for Multinomial Diffusion and Masked Generative Models—0
DICE: Distilling Classifier-Free Guidance into Text Embeddings—0
CacheQuant: Comprehensively Accelerated Diffusion Models—0
DiCTI: Diffusion-based Clothing Designer via Text-guided Input—0
Reconstruct Spine CT from Biplanar X-Rays via Diffusion Learning—0
Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models—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