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 4101–4150 of 6689 papers

TitleStatusHype
Post-Training Quantization for Diffusion Transformer via Hierarchical Timestep Grouping—0
Potential Auto-driving Threat: Universal Rain-removal Attack—0
Ambient Denoising Diffusion Generative Adversarial Networks for Establishing Stochastic Object Models from Noisy Image Data—0
PQD: Post-training Quantization for Efficient Diffusion Models—0
3D-Aware Facial Landmark Detection via Multi-View Consistent Training on Synthetic Data—0
Practical Digital Disguises: Leveraging Face Swaps to Protect Patient Privacy—0
PreciseCam: Precise Camera Control for Text-to-Image Generation—0
Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation—0
Unlearnable Examples for Diffusion Models: Protect Data from Unauthorized Exploitation—0
Predicated Diffusion: Predicate Logic-Based Attention Guidance for Text-to-Image Diffusion Models—0
Prediction with Action: Visual Policy Learning via Joint Denoising Process—0
Preference Alignment on Diffusion Model: A Comprehensive Survey for Image Generation and Editing—0
Zero-shot spatial layout conditioning for text-to-image diffusion models—0
Preliminary Explorations with GPT-4o(mni) Native Image Generation—0
Zero-Shot Styled Text Image Generation, but Make It Autoregressive—0
Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models—0
Pre-trained Language Models Do Not Help Auto-regressive Text-to-Image Generation—0
Preventing Posterior Collapse with delta-VAEs—0
Primal and Dual Analysis of Entropic Fictitious Play for Finite-sum Problems—0
Principal Component Density Estimation for Scenario Generation Using Normalizing Flows—0
Principled Out-of-Distribution Generalization via Simplicity—0
Prioritize Denoising Steps on Diffusion Model Preference Alignment via Explicit Denoised Distribution Estimation—0
PriorityCut: Occlusion-aware Regularization for Image Animation—0
Prior Learning in Introspective VAEs—0
PRISM: A Unified Framework for Photorealistic Reconstruction and Intrinsic Scene Modeling—0
PRISM: Progressive Restoration for Scene Graph-based Image Manipulation—0
PrivacyGAN: robust generative image privacy—0
Words Worth a Thousand Pictures: Measuring and Understanding Perceptual Variability in Text-to-Image Generation—0
Privacy Protection Against Personalized Text-to-Image Synthesis via Cross-image Consistency Constraints—0
Privacy Threats in Stable Diffusion Models—0
Private Image Generation With Dual-Purpose Auxiliary Classifier—0
TP2O: Creative Text Pair-to-Object Generation using Balance Swap-Sampling—0
World-consistent Video Diffusion with Explicit 3D Modeling—0
Probabilistic Semantic Embedding—0
Probing TryOnGAN—0
Procedural Modeling and Physically Based Rendering for Synthetic Data Generation in Automotive Applications—0
Process-aware and high-fidelity microstructure generation using stable diffusion—0
A Maximum A Posteriori Estimation Framework for Robust High Dynamic Range Video Synthesis—0
Processsing Simple Geometric Attributes with Autoencoders—0
Pro-DG: Procedural Diffusion Guidance for Architectural Facade Generation—0
Programmable-Room: Interactive Textured 3D Room Meshes Generation Empowered by Large Language Models—0
WorldGenBench: A World-Knowledge-Integrated Benchmark for Reasoning-Driven Text-to-Image Generation—0
Progressive Compression with Universally Quantized Diffusion Models—0
Unlimited Resolution Image Generation with R2D2-GANs—0
Progressive Text-to-Image Generation—0
Progressive distillation diffusion for raw music generation—0
Altogether: Image Captioning via Re-aligning Alt-text—0
Alteration-free and Model-agnostic Origin Attribution of Generated Images—0
Progressively Growing Generative Adversarial Networks for High Resolution Semantic Segmentation of Satellite Images—0
Progressively Unfreezing Perceptual GAN—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