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 3101–3150 of 6689 papers

TitleStatusHype
Imaginative Walks: Generative Random Walk Deviation Loss for Improved Unseen Learning RepresentationCode0
Implicit Dynamical Flow Fusion (IDFF) for Generative ModelingCode0
Complex Image Generation SwinTransformer Network for Audio DenoisingCode0
Image Translation for Medical Image Generation -- Ischemic Stroke LesionsCode0
Emerging Convolutions for Generative Normalizing FlowsCode0
Compensation Sampling for Improved Convergence in Diffusion ModelsCode0
Implicit Generation and Modeling with Energy Based ModelsCode0
Images Speak Volumes: User-Centric Assessment of Image Generation for Accessible CommunicationCode0
Image Style Transfer Using Convolutional Neural NetworksCode0
Eliminating Contextual Prior Bias for Semantic Image Editing via Dual-Cycle DiffusionCode0
Image Processing Using Multi-Code GAN PriorCode0
EliGen: Entity-Level Controlled Image Generation with Regional AttentionCode0
Detecting Out-of-Context Image-Caption Pairs in News: A Counter-Intuitive MethodCode0
ASPIRE: Language-Guided Data Augmentation for Improving Robustness Against Spurious CorrelationsCode0
Image Inpainting via Tractable Steering of Diffusion ModelsCode0
Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial NetworksCode0
Implicit Generative CopulasCode0
SkipVAR: Accelerating Visual Autoregressive Modeling via Adaptive Frequency-Aware SkippingCode0
Enhancing CT Image synthesis from multi-modal MRI data based on a multi-task neural network framework—0
ComfyGPT: A Self-Optimizing Multi-Agent System for Comprehensive ComfyUI Workflow Generation—0
Efficient-VQGAN: Towards High-Resolution Image Generation with Efficient Vision Transformers—0
ComfyGI: Automatic Improvement of Image Generation Workflows—0
Efficient Transfer Learning in Diffusion Models via Adversarial Noise—0
ComfyGen: Prompt-Adaptive Workflows for Text-to-Image Generation—0
Efficient Training with Denoised Neural Weights—0
Efficient training for future video generation based on hierarchical disentangled representation of latent variables—0
Combining Transformer Generators with Convolutional Discriminators—0
A Flexible Measurement of Diversity in Datasets with Random Network Distillation—0
Efficient Scaling of Diffusion Transformers for Text-to-Image Generation—0
Efficient Quantization Strategies for Latent Diffusion Models—0
Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection—0
Efficient Pruning of Text-to-Image Models: Insights from Pruning Stable Diffusion—0
Combining Generative Artificial Intelligence (AI) and the Internet: Heading towards Evolution or Degradation?—0
Combining Attention with Flow for Person Image Synthesis—0
Affordance Diffusion: Synthesizing Hand-Object Interactions—0
Efficient Multi-Instance Generation with Janus-Pro-Dirven Prompt Parsing—0
Combinets: Creativity via Recombination of Neural Networks—0
Efficient Listener: Dyadic Facial Motion Synthesis via Action Diffusion—0
A Simple Background Augmentation Method for Object Detection with Diffusion Model—0
Efficient Hair Style Transfer with Generative Adversarial Networks—0
Combating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues—0
Efficient Generative Modeling with Residual Vector Quantization-Based Tokens—0
A Simple Approach to Unifying Diffusion-based Conditional Generation—0
Affective Image Filter: Reflecting Emotions from Text to Images—0
Efficient Flow Matching using Latent Variables—0
Efficient Exploration of Image Classifier Failures with Bayesian Optimization and Text-to-Image Models—0
Color Correction Meets Cross-Spectral Refinement: A Distribution-Aware Diffusion for Underwater Image Restoration—0
Efficient Diffusion Training through Parallelization with Truncated Karhunen-Loève Expansion—0
Color Alignment in Diffusion—0
AffectGAN: Affect-Based Generative Art Driven by Semantics—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