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 5026–5050 of 6689 papers

TitleStatusHype
CrossViewDiff: A Cross-View Diffusion Model for Satellite-to-Street View Synthesis—0
StEP: Style-based Encoder Pre-training for Multi-modal Image Synthesis—0
A Deep Generative Deconvolutional Image Model—0
Cross-View Image Synthesis with Deformable Convolution and Attention Mechanism—0
Make VLM Recognize Visual Hallucination on Cartoon Character Image with Pose Information—0
StereoGen: High-quality Stereo Image Generation from a Single Image—0
Efficient Visualization of Neural Networks with Generative Models and Adversarial Perturbations—0
Cartoondiff: Training-free Cartoon Image Generation with Diffusion Transformer Models—0
Stereotypes and Smut: The (Mis)representation of Non-cisgender Identities by Text-to-Image Models—0
CSG: A Context-Semantic Guided Diffusion Approach in De Novo Musculoskeletal Ultrasound Image Generation—0
CSGO: Content-Style Composition in Text-to-Image Generation—0
CTGAN: Semantic-guided Conditional Texture Generator for 3D Shapes—0
CT Image Synthesis Using Weakly Supervised Segmentation and Geometric Inter-Label Relations For COVID Image Analysis—0
Ctrl-Adapter: An Efficient and Versatile Framework for Adapting Diverse Controls to Any Diffusion Model—0
CtrlNeRF: The Generative Neural Radiation Fields for the Controllable Synthesis of High-fidelity 3D-Aware Images—0
CTRL-O: Language-Controllable Object-Centric Visual Representation Learning—0
CART: Compositional Auto-Regressive Transformer for Image Generation—0
Ctrl-U: Robust Conditional Image Generation via Uncertainty-aware Reward Modeling—0
Ctrl-X: Controlling Structure and Appearance for Text-To-Image Generation Without Guidance—0
CT Synthesis with Conditional Diffusion Models for Abdominal Lymph Node Segmentation—0
Culture-TRIP: Culturally-Aware Text-to-Image Generation with Iterative Prompt Refinement—0
Cumulant GAN—0
Current State of Community-Driven Radiological AI Deployment in Medical Imaging—0
Cardiac ultrasound simulation for autonomous ultrasound navigation—0
A Deep Bayesian Nonparametric Framework for Robust Mutual Information Estimation—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