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 5901–5950 of 6689 papers

TitleStatusHype
Image Augmentations for GAN Training—0
Nested Scale Editing for Conditional Image Synthesis—0
Attack to Explain Deep Representation—0
Nested Scale-Editing for Conditional Image Synthesis—0
Transformation GAN for Unsupervised Image Synthesis and Representation Learning—0
MISC: Multi-Condition Injection and Spatially-Adaptive Compositing for Conditional Person Image Synthesis—0
Geometry-Aware Satellite-to-Ground Image Synthesis for Urban Areas—0
CookGAN: Causality Based Text-to-Image Synthesis—0
Regularizing Discriminative Capability of CGANs for Semi-Supervised Generative Learning—0
RiFeGAN: Rich Feature Generation for Text-to-Image Synthesis From Prior Knowledge—0
Exemplar-based Generative Facial Editing—0
Deep super resolution crack network (SrcNet) for improving computer vision–based automated crack detectability in in situ bridges—0
Region-adaptive Texture Enhancement for Detailed Person Image SynthesisCode0
Bayesian Conditional GAN for MRI Brain Image Synthesis—0
SegAttnGAN: Text to Image Generation with Segmentation Attention—0
Interpreting the Latent Space of GANs via Correlation Analysis for Controllable Concept Manipulation—0
Medical Image Generation using Generative Adversarial Networks—0
Co-occurrence Based Texture SynthesisCode0
Visual Relationship Detection using Scene Graphs: A Survey—0
deepSELF: An Open Source Deep Self End-to-End Learning Framework—0
Medical Image Segmentation Using a U-Net type of Architecture—0
Deep convolutional generative adversarial networks for traffic data imputation encoding time series as images—0
Generative Adversarial Data Programming—0
EM-GAN: Fast Stress Analysis for Multi-Segment Interconnect Using Generative Adversarial Networks—0
Evaluation Metrics for Conditional Image Generation—0
Stomach 3D Reconstruction Based on Virtual Chromoendoscopic Image Generation—0
DeepFake Detection by Analyzing Convolutional Traces—0
Panoptic-based Image Synthesis—0
Cosmetic-Aware Makeup Cleanser—0
Quality Guided Sketch-to-Photo Image SynthesisCode0
Halluci-Net: Scene Completion by Exploiting Object Co-occurrence Relationships—0
Example-Guided Image Synthesis across Arbitrary Scenes using Masked Spatial-Channel Attention and Self-Supervision—0
Calibrated Vehicle Paint Signatures for Simulating Hyperspectral Imagery—0
ControlVAE: Controllable Variational Autoencoder—0
Learning Spatial Relationships between Samples of Patent Image Shapes—0
Self-Supervised 3D Human Pose Estimation via Part Guided Novel Image Synthesis—0
State of the Art on Neural Rendering—0
Coarse-to-Fine Gaze Redirection with Numerical and Pictorial GuidanceCode0
Training End-to-end Single Image Generators without GANs—0
Rethinking Spatially-Adaptive Normalization—0
Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the DiscriminatorCode0
Open Domain Dialogue Generation with Latent Images—0
Theoretical Insights into the Use of Structural Similarity Index In Generative Models and Inferential Autoencoders—0
A New Dataset and Boundary-Attention Semantic Segmentation for Face Parsing—0
Object-Centric Image Generation with Factored Depths, Locations, and Appearances—0
Synthesis and Edition of Ultrasound Images via Sketch Guided Progressive Growing GANs—0
Learning Generative Models of Tissue Organization with Supervised GANsCode0
Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation—0
Lesion Conditional Image Generation for Improved Segmentation of Intracranial Hemorrhage from CT Images—0
Image Generation Via Minimizing Fréchet Distance in Discriminator Feature SpaceCode0
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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