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 5701–5750 of 6689 papers

TitleStatusHype
Density-aware Haze Image Synthesis by Self-Supervised Content-Style Disentanglement—0
HumanGAN: A Generative Model of Humans Images—0
Robustness Evaluation of Stacked Generative Adversarial Networks using Metamorphic Testing—0
Deblurring Processor for Motion-Blurred Faces Based on Generative Adversarial Networks—0
M6: A Chinese Multimodal Pretrainer—0
Energy-based Models for Earth Observation Applications—0
Style and Pose Control for Image Synthesis of Humans from a Single Monocular View—0
Kanerva++: extending The Kanerva Machine with differentiable, locally block allocated latent memory—0
Pose Guided Person Image Generation with Hidden p-Norm Regression—0
Evolving GAN Formulations for Higher Quality Image Synthesis—0
Enhanced Magnetic Resonance Image Synthesis with Contrast-Aware Generative Adversarial Networks—0
Just Noticeable Difference for Machine Perception and Generation of Regularized Adversarial Images with Minimal Perturbation—0
Hyperbolic Generative Adversarial Network—0
SAM-GAN: Self-Attention supporting Multi-stage Generative Adversarial Networks for text-to-image synthesis—0
Diverse Single Image Generation with Controllable Global Structure—0
Template-Free Try-on Image Synthesis via Semantic-guided Optimization—0
Structure-aware Person Image Generation with Pose Decomposition and Semantic Correlation—0
TricycleGAN: Unsupervised Image Synthesis and Segmentation Based on Shape Priors—0
UPHDR-GAN: Generative Adversarial Network for High Dynamic Range Imaging with Unpaired Data—0
Self Sparse Generative Adversarial Networks—0
Adversarial Text-to-Image Synthesis: A Review—0
Generative Zero-shot Network Quantization—0
Image-to-Image Translation: Methods and Applications—0
DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training—0
Adversarial cycle-consistent synthesis of cerebral microbleeds for data augmentation—0
Non-uniform Motion Deblurring with Blurry Component Divided Guidance—0
A Pipeline for Vision-Based On-Orbit Proximity Operations Using Deep Learning and Synthetic Imagery—0
Dual-cycle Constrained Bijective VAE-GAN For Tagged-to-Cine Magnetic Resonance Image Synthesis—0
Fine-grained Semantic Constraint in Image Synthesis—0
Cycle Generative Adversarial Networks Algorithm With Style Transfer For Image Generation—0
ArrowGAN : Learning to Generate Videos by Learning Arrow of Time—0
Synthetic Glacier SAR Image Generation from Arbitrary Masks Using Pix2Pix Algorithm—0
Guiding GANs: How to control non-conditional pre-trained GANs for conditional image generation—0
Generative Max-Mahalanobis Classifiers for Image Classification, Generation and MoreCode0
LayoutTransformer: Relation-Aware Scene Layout Generation—0
MVP: Multivariate polynomials for conditional generation—0
HYPE-C: Evaluating Image Completion Models Through Standardized Crowdsourcing—0
Learning Energy-Based Generative Models via Coarse-to-Fine Expanding and Sampling—0
not-so-big-GAN: Generating High-Fidelity Images on Small Compute with Wavelet-based Super-Resolution—0
A Probabilistic Approach to Constrained Deep Clustering—0
Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained Image Generation—0
Unconditional Synthesis of Complex Scenes Using a Semantic Bottleneck—0
PriorityCut: Occlusion-aware Regularization for Image Animation—0
Structure-Transformed Texture-Enhanced Network for Person Image Synthesis—0
Biologically Inspired Hexagonal Deep Learning for Hexagonal Image Generation—0
Membership Attacks on Conditional Generative Models Using Image Difficulty—0
FREA-Unet: Frequency-aware U-net for Modality Transfer—0
Vid2Actor: Free-viewpoint Animatable Person Synthesis from Video in the Wild—0
Correspondence Learning for Controllable Person Image Generation—0
Evaluating GAN-Based Image Augmentation for Threat Detection in Large-Scale Xray Security Images—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