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

Showing 53015350 of 6689 papers

TitleStatusHype
Adaptive Multi-modal Fusion of Spatially Variant Kernel Refinement with Diffusion Model for Blind Image Super-Resolution0
Diffuse and Disperse: Image Generation with Representation Regularization0
Adaptively-Realistic Image Generation from Stroke and Sketch with Diffusion Model0
Vision-Language Matching for Text-to-Image Synthesis via Generative Adversarial Networks0
DiffuseGAE: Controllable and High-fidelity Image Manipulation from Disentangled Representation0
DiffuseKronA: A Parameter Efficient Fine-tuning Method for Personalized Diffusion Models0
DiffuseRAW: End-to-End Generative RAW Image Processing for Low-Light Images0
BRICS: Bi-level feature Representation of Image CollectionS0
Bridging the gap between AI and Healthcare sides: towards developing clinically relevant AI-powered diagnosis systems0
Bridging Generative and Discriminative Models for Unified Visual Perception with Diffusion Priors0
DiffusionAct: Controllable Diffusion Autoencoder for One-shot Face Reenactment0
Diffusion Autoencoders are Scalable Image Tokenizers0
Diffusion Autoencoders for Few-shot Image Generation in Hyperbolic Space0
Vision-Language Modeling Meets Remote Sensing: Models, Datasets and Perspectives0
Diffusion-Based Approaches in Medical Image Generation and Analysis0
Adaptively Controllable Diffusion Model for Efficient Conditional Image Generation0
Style transfer-based image synthesis as an efficient regularization technique in deep learning0
Diffusion-based Data Augmentation for Skin Disease Classification: Impact Across Original Medical Datasets to Fully Synthetic Images0
Diffusion-based generation of Histopathological Whole Slide Images at a Gigapixel scale0
Stylish and Functional: Guided Interpolation Subject to Physical Constraints0
Stylized Projected GAN: A Novel Architecture for Fast and Realistic Image Generation0
Diffusion-Based Speech Enhancement in Matched and Mismatched Conditions Using a Heun-Based Sampler0
Diffusion Beats Autoregressive: An Evaluation of Compositional Generation in Text-to-Image Models0
DiffusionBlocks: Blockwise Training for Generative Models via Score-Based Diffusion0
Adaptive Cyclic Diffusion for Inference Scaling0
Subject-driven Text-to-Image Generation via Apprenticeship Learning0
You Only Submit One Image to Find the Most Suitable Generative Model0
DiffUMI: Training-Free Universal Model Inversion via Unconditional Diffusion for Face Recognition0
Bridging CLIP and StyleGAN through Latent Alignment for Image Editing0
BRIDGING ADVERSARIAL SAMPLES AND ADVERSARIAL NETWORKS0
Vision-Language Models Represent Darker-Skinned Black Individuals as More Homogeneous than Lighter-Skinned Black Individuals0
Bridge Diffusion Model: bridge non-English language-native text-to-image diffusion model with English communities0
SuperNeRF-GAN: A Universal 3D-Consistent Super-Resolution Framework for Efficient and Enhanced 3D-Aware Image Synthesis0
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images0
DiffusionGPT: LLM-Driven Text-to-Image Generation System0
Diffusion idea exploration for art generation0
Your Autoregressive Generative Model Can be Better If You Treat It as an Energy-Based One0
Diffusion Instruction Tuning0
Diffusion Lens: Interpreting Text Encoders in Text-to-Image Pipelines0
BraSyn 2023 challenge: Missing MRI synthesis and the effect of different learning objectives0
Diffusion Model Conditioning on Gaussian Mixture Model and Negative Gaussian Mixture Gradient0
Supervised Adversarial Networks for Image Saliency Detection0
Diffusion Models as Data Mining Tools0
PanoFree: Tuning-Free Holistic Multi-view Image Generation with Cross-view Self-Guidance0
BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity0
Diffusion Models Enable Zero-Shot Pose Estimation for Lower-Limb Prosthetic Users0
Vision Reimagined: AI-Powered Breakthroughs in WiFi Indoor Imaging0
Diffusion models for Gaussian distributions: Exact solutions and Wasserstein errors0
Surf-CDM: Score-Based Surface Cold-Diffusion Model For Medical Image Segmentation0
Brain Image Synthesis With Unsupervised Multivariate Canonical CSCl4Net0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Improved DDPMFID12.3Unverified
2ADMFID11.84Unverified
3BigGAN-deepFID8.1Unverified
4Polarity-BigGANFID6.82Unverified
5VQGAN+Transformer (k=mixed, p=1.0, a=0.005)FID6.59Unverified
6MaskGITFID6.18Unverified
7VQGAN+Transformer (k=600, p=1.0, a=0.05)FID5.2Unverified
8CDMFID4.88Unverified
9ADM-GFID4.59Unverified
10RINFID4.51Unverified
#ModelMetricClaimedVerifiedStatus
1PresGANFID52.2Unverified
2RESFLOWFID48.29Unverified
3Residual FlowFID46.37Unverified
4GLF+perceptual loss (ours)FID44.6Unverified
5ProdPoly no activation functionsFID40.45Unverified
6ProdPoly no activation functionsFID36.77Unverified
7ACGANFID35.47Unverified
8DenseFlow-74-10FID34.9Unverified
9NVAE w/ flowFID32.53Unverified
10QSNGANFID31.97Unverified
#ModelMetricClaimedVerifiedStatus
1GLIDE + CLSFID30.87Unverified
2GLIDE + CLIPFID30.46Unverified
3GLIDE + CLS-FREEFID29.22Unverified
4GLIDE + CLIP + CLS + CLS-FREEFID29.18Unverified
5PGMGANFID21.73Unverified
6CLR-GANFID20.27Unverified
7FMFID14.45Unverified
8CT (Direct Generation, NFE=1)FID13Unverified
9CT (Direct Generation, NFE=2)FID11.1Unverified
10GLIDE +CLSKID7.95Unverified