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 2301–2350 of 6689 papers

TitleStatusHype
Training Generative Adversarial Networks via stochastic Nash games—0
DreamBlend: Advancing Personalized Fine-tuning of Text-to-Image Diffusion Models—0
Classification under strategic adversary manipulation using pessimistic bilevel optimisation—0
DreamArtist++: Controllable One-Shot Text-to-Image Generation via Positive-Negative Adapter—0
Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Models—0
Classification Diffusion Models: Revitalizing Density Ratio Estimation—0
A Robust Pose Transformational GAN for Pose Guided Person Image Synthesis—0
DRDM: A Disentangled Representations Diffusion Model for Synthesizing Realistic Person Images—0
DRC: Enhancing Personalized Image Generation via Disentangled Representation Composition—0
Adversarial Pixel-Level Generation of Semantic Images—0
DrawingInStyles: Portrait Image Generation and Editing with Spatially Conditioned StyleGAN—0
Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey—0
Generative Adversarial Networks Conditioned by Brain Signals—0
DragTraffic: Interactive and Controllable Traffic Scene Generation for Autonomous Driving—0
Clarifying MCMC-based training of modern EBMs : Contrastive Divergence versus Maximum Likelihood—0
Drag-guided diffusion models for vehicle image generation—0
Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer—0
Circuit Complexity Bounds for Visual Autoregressive Model—0
ARMOR v0.1: Empowering Autoregressive Multimodal Understanding Model with Interleaved Multimodal Generation via Asymmetric Synergy—0
Dr.3D: Adapting 3D GANs to Artistic Drawings—0
CipherDM: Secure Three-Party Inference for Diffusion Model Sampling—0
Adversarial nets with perceptual losses for text-to-image synthesis—0
CIMGEN: Controlled Image Manipulation by Finetuning Pretrained Generative Models on Limited Data—0
DPDEdit: Detail-Preserved Diffusion Models for Multimodal Fashion Image Editing—0
Chinese Typeface Transformation with Hierarchical Adversarial Network—0
DPCL-Diff: The Temporal Knowledge Graph Reasoning Based on Graph Node Diffusion Model with Dual-Domain Periodic Contrastive Learning—0
DPAF: Image Synthesis via Differentially Private Aggregation in Forward Phase—0
Multimodal Cinematic Video Synthesis Using Text-to-Image and Audio Generation Models—0
DOTE: Dual cOnvolutional filTer lEarning for Super-Resolution and Cross-Modality Synthesis in MRI—0
DoodleFormer: Creative Sketch Drawing with Transformers—0
Don't Forget your Inverse DDIM for Image Editing—0
Do Not Mask What You Do Not Need to Mask: a Parser-Free Virtual Try-On—0
Chop & Learn: Recognizing and Generating Object-State Compositions—0
Generative Adversarial Data Programming—0
Generative Adversarial Image Synthesis with Decision Tree Latent Controller—0
Generation and Simulation of Yeast Microscopy Imagery with Deep Learning—0
Domain Generalization for 6D Pose Estimation Through NeRF-based Image Synthesis—0
Chili Pepper Disease Diagnosis via Image Reconstruction Using GrabCut and Generative Adversarial Serial Autoencoder—0
Generation of Anonymous Chest Radiographs Using Latent Diffusion Models for Training Thoracic Abnormality Classification Systems—0
Chest-Diffusion: A Light-Weight Text-to-Image Model for Report-to-CXR Generation—0
Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Models—0
Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging—0
Domain Adaptation Using Adversarial Learning for Autonomous Navigation—0
Accelerating Diffusion Models with One-to-Many Knowledge Distillation—0
Generation of Synthetic Images for Pedestrian Detection Using a Sequence of GANs—0
Do I look like a `cat.n.01` to you? A Taxonomy Image Generation Benchmark—0
Does CLIP perceive art the same way we do?—0
Check Locate Rectify: A Training-Free Layout Calibration System for Text-to-Image Generation—0
Do Distributed Semantic Models Dream of Electric Sheep? Visualizing Word Representations through Image Synthesis—0
On Error Propagation of 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