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 6551–6600 of 6689 papers

TitleStatusHype
Self-supervised monocular depth estimation from oblique UAV videosCode0
Design a Delicious Lunchbox in StyleCode0
Self-Supervised Object Detection via Generative Image SynthesisCode0
High-Resolution Deep Convolutional Generative Adversarial NetworksCode0
Artificial Generation of Big Data for Improving Image Classification: A Generative Adversarial Network Approach on SAR DataCode0
LumiPath -- Towards Real-time Physically-based Rendering on Embedded DevicesCode0
Self-Supervised One-Shot Learning for Automatic Segmentation of StyleGAN ImagesCode0
AAD-DCE: An Aggregated Multimodal Attention Mechanism for Early and Late Dynamic Contrast Enhanced Prostate MRI SynthesisCode0
Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information FlowCode0
DeCoDEx: Confounder Detector Guidance for Improved Diffusion-based Counterfactual ExplanationsCode0
DEsignBench: Exploring and Benchmarking DALL-E 3 for Imagining Visual DesignCode0
High-Resolution Network for Photorealistic Style TransferCode0
High-resolution Rainy Image Synthesis: Learning from RenderingCode0
M3Dsynth: A dataset of medical 3D images with AI-generated local manipulationsCode0
Self-Supervised Ultrasound to MRI Fetal Brain Image SynthesisCode0
DeSIGN: Design Inspiration from Generative NetworksCode0
Open-Source Acceleration of Stable-Diffusion.cpp Deployable on All DevicesCode0
Understanding Visual Concepts Across ModelsCode0
Angio-Diff: Learning a Self-Supervised Adversarial Diffusion Model for Angiographic Geometry GenerationCode0
Synthesizing Images of Humans in Unseen PosesCode0
MACS: Multi-source Audio-to-image Generation with Contextual Significance and Semantic AlignmentCode0
Calibrating Energy-based Generative Adversarial NetworksCode0
Semantically Decomposing the Latent Spaces of Generative Adversarial NetworksCode0
RecTable: Fast Modeling Tabular Data with Rectified FlowCode0
Histopathology DatasetGAN: Synthesizing Large-Resolution Histopathology DatasetsCode0
MAGAN: Margin Adaptation for Generative Adversarial NetworksCode0
Hita: Holistic Tokenizer for Autoregressive Image GenerationCode0
StyleT2F: Generating Human Faces from Textual Description Using StyleGAN2Code0
Magic 1-For-1: Generating One Minute Video Clips within One MinuteCode0
Distribution Matching Losses Can Hallucinate Features in Medical Image TranslationCode0
ArtGAN: Artwork Synthesis with Conditional Categorical GANsCode0
Recursive Reasoning in Minimax Games: A Level k Gradient Play MethodCode0
HoloGAN: Unsupervised learning of 3D representations from natural imagesCode0
Optimal Eye Surgeon: Finding Image Priors through Sparse Generators at InitializationCode0
Optimal Linear Subspace Search: Learning to Construct Fast and High-Quality Schedulers for Diffusion ModelsCode0
A New Paradigm for Generative Adversarial Networks based on Randomized Decision RulesCode0
How Control Information Influences Multilingual Text Image Generation and Editing?Code0
MAGIC: Mask-Guided Image Synthesis by Inverting a Quasi-Robust ClassifierCode0
Semantic Approach to Quantifying the Consistency of Diffusion Model Image GenerationCode0
Semantic-aware Data Augmentation for Text-to-image SynthesisCode0
Generalized Compressed Sensing for Image Reconstruction with Diffusion Probabilistic ModelsCode0
Decontextualized learning for interpretable hierarchical representations of visual patternsCode0
Towards Segment Anything Model (SAM) for Medical Image Segmentation: A SurveyCode0
Semantic-aware Network for Aerial-to-Ground Image SynthesisCode0
How to Backdoor Consistency Models?Code0
Semantic Bottleneck Scene GenerationCode0
Synthetic Trajectory Generation Through Convolutional Neural NetworksCode0
Unsupervised Holistic Image Generation from Key Local PatchesCode0
Energy-Calibrated VAE with Test Time Free LunchCode0
ArtAug: Enhancing Text-to-Image Generation through Synthesis-Understanding InteractionCode0
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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