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 5451–5500 of 6689 papers

TitleStatusHype
CG-NeRF: Conditional Generative Neural Radiance Fields—0
DoodleFormer: Creative Sketch Drawing with Transformers—0
Encouraging Disentangled and Convex Representation with Controllable Interpolation Regularization—0
Panoptic-aware Image-to-Image Translation—0
Global Context with Discrete Diffusion in Vector Quantised Modelling for Image Generation—0
Image Generation using Continuous Filter Atoms—0
GLocal: Global Graph Reasoning and Local Structure Transfer for Person Image Generation—0
Conditional Generation Using Polynomial ExpansionsCode0
Exploration into Translation-Equivariant Image QuantizationCode0
FDA-GAN: Flow-based Dual Attention GAN for Human Pose Transfer—0
GANORCON: Are Generative Models Useful for Few-shot Segmentation?—0
Highly accelerated MR parametric mapping by undersampling the k-space and reducing the contrast number simultaneously with deep learning—0
Generative Convolution Layer for Image Generation—0
Human Imperceptible Attacks and Applications to Improve Fairness—0
Trust the Critics: Generatorless and Multipurpose WGANs with Initial Convergence GuaranteesCode0
Self-supervised Correlation Mining Network for Person Image Generation—0
Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey—0
A Novel Framework for Image-to-image Translation and Image Compression—0
MixSyn: Learning Composition and Style for Multi-Source Image Synthesis—0
Tensor Component Analysis for Interpreting the Latent Space of GANs—0
Delving into Rectifiers in Style-Based Image Translation—0
DiverGAN: An Efficient and Effective Single-Stage Framework for Diverse Text-to-Image Generation—0
Things not Written in Text: Exploring Spatial Commonsense from Visual Signals—0
Generating a Temporally Coherent Image Sequence for a Story by Multimodal Recurrent Transformers—0
A Multi-attribute Controllable Generative Model for Histopathology Image SynthesisCode0
Template NeRF: Towards Modeling Dense Shape Correspondences from Category-Specific Object Images—0
Estimating High Order Gradients of the Data Distribution by Denoising—0
NeurInt : Learning to Interpolate through Neural ODEs—0
Improving Visual Quality of Image Synthesis by A Token-based Generator with Transformers—0
A Deep Learning Generative Model Approach for Image Synthesis of Plant Leaves—0
GraN-GAN: Piecewise Gradient Normalization for Generative Adversarial Networks—0
Adversarially Perturbed Wavelet-based Morphed Face Generation—0
3-D PET Image Generation with tumour masks using TGANCode0
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training—0
MOST-GAN: 3D Morphable StyleGAN for Disentangled Face Image Manipulation—0
Counter-Contrastive Learning for Language GANs—0
Sketch-to-Car: Synthesizing Stylized Car Images From SketchesCode0
Multivariate rank via entropic optimal transport: sample efficiency and generative modelingCode0
Sharp-GAN: Sharpness Loss Regularized GAN for Histopathology Image Synthesis—0
Raw Bayer Pattern Image Synthesis for Computer Vision-oriented Image Signal Processing Pipeline Design—0
The Nuts and Bolts of Adopting Transformer in GANs—0
Face sketch to photo translation using generative adversarial networks—0
Multi-attribute Pizza Generator: Cross-domain Attribute Control with Conditional StyleGANCode0
EvoGAN: An Evolutionary Computation Assisted GANCode0
MIGS: Meta Image Generation from Scene GraphsCode0
Efficient Gradient Flows in Sliced-Wasserstein SpaceCode0
Fine-Grained Control of Artistic Styles in Image Generation—0
Self-Supervised Object Detection via Generative Image SynthesisCode0
Continuation of Famous Art with AI: A Conditional Adversarial Network Inpainting Approach—0
Distinguishing Natural and Computer-Generated Images using Multi-Colorspace fused EfficientNetCode0
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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