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 4251–4300 of 6689 papers

TitleStatusHype
3D-Aware Generative Model for Improved Side-View Image Synthesis—0
Foreground-Background Separation through Concept Distillation from Generative Image Foundation ModelsCode1
HairNeRF: Geometry-Aware Image Synthesis for Hairstyle Transfer—0
Affective Image Filter: Reflecting Emotions from Text to Images—0
Personalized Image Generation for Color Vision Deficiency PopulationCode0
Controllable Person Image Synthesis with Pose-Constrained Latent Diffusion—0
Neural Characteristic Function Learning for Conditional Image GenerationCode0
What can Discriminator do? Towards Box-free Ownership Verification of Generative Adversarial NetworksCode0
SIDGAN: High-Resolution Dubbed Video Generation via Shift-Invariant Learning—0
RWSC-Fusion: Region-Wise Style-Controlled Fusion Network for the Prohibited X-Ray Security Image Synthesis—0
PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360degCode3
Learning on Gradients: Generalized Artifacts Representation for GAN-Generated Images DetectionCode1
Quantitative Manipulation of Custom Attributes on 3D-Aware Image Synthesis—0
Re-GAN: Data-Efficient GANs Training via Architectural ReconfigurationCode1
Specialist Diffusion: Plug-and-Play Sample-Efficient Fine-Tuning of Text-to-Image Diffusion Models To Learn Any Unseen StyleCode0
Private Image Generation With Dual-Purpose Auxiliary Classifier—0
Exploring Intra-Class Variation Factors With Learnable Cluster Prompts for Semi-Supervised Image Synthesis—0
RIATIG: Reliable and Imperceptible Adversarial Text-to-Image Generation With Natural PromptsCode1
Where Is My Spot? Few-Shot Image Generation via Latent Subspace OptimizationCode1
3D-Aware Facial Landmark Detection via Multi-View Consistent Training on Synthetic Data—0
eVAE: Evolutionary Variational AutoencoderCode2
GAFNet: A Global Fourier Self Attention Based Novel Network for multi-modal downstream tasks—0
Ponder: Point Cloud Pre-training via Neural Rendering—0
Image Embedding for Denoising Generative ModelsCode0
Current State of Community-Driven Radiological AI Deployment in Medical Imaging—0
OrthoGAN:High-Precision Image Generation for Teeth Orthodontic Visualization—0
Discriminator-Cooperated Feature Map Distillation for GAN CompressionCode1
Zero-Shot Object Segmentation through Concept Distillation from Generative Image Foundation Models—0
PointVST: Self-Supervised Pre-training for 3D Point Clouds via View-Specific Point-to-Image TranslationCode1
Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Models—0
SynCLay: Interactive Synthesis of Histology Images from Bespoke Cellular LayoutsCode1
Exploring Transformer Backbones for Image Diffusion Models—0
Application of Unsupervised Domain Adaptation for Structural MRI Analysis—0
Do DALL-E and Flamingo Understand Each Other?—0
Hybrid Quantum-Classical Generative Adversarial Network for High Resolution Image GenerationCode1
DisCoScene: Spatially Disentangled Generative Radiance Fields for Controllable 3D-aware Scene Synthesis—0
Scalable Adaptive Computation for Iterative GenerationCode0
FunkNN: Neural Interpolation for Functional GenerationCode1
Local Differential Privacy Image Generation Using Flow-based Deep Generative Models—0
Unified Framework for Histopathology Image Augmentation and Classification via Generative Models—0
Character-Aware Models Improve Visual Text RenderingCode2
Benchmarking Spatial Relationships in Text-to-Image GenerationCode1
MetaCLUE: Towards Comprehensive Visual Metaphors Research—0
Scalable Diffusion Models with TransformersCode5
Speed up the inference of diffusion models via shortcut MCMC sampling—0
Human Image Generation: A Comprehensive Survey—0
DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic ModelsCode1
Fake it till you make it: Learning transferable representations from synthetic ImageNet clones—0
SADM: Sequence-Aware Diffusion Model for Longitudinal Medical Image GenerationCode1
Benchmarking Robustness of Multimodal Image-Text Models under Distribution ShiftCode1
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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