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 2951–3000 of 6689 papers

TitleStatusHype
GRAM: Generative Radiance Manifolds for 3D-Aware Image Generation—0
Deep Domain-Adversarial Image Generation for Domain Generalisation—0
Bidirectional Brain Image Translation using Transfer Learning from Generic Pre-trained Models—0
Gradpaint: Gradient-Guided Inpainting with Diffusion Models—0
Deep Diffusion Models and Unsupervised Hyperspectral Unmixing for Realistic Abundance Map Synthesis—0
Hierarchical Modes Exploring in Generative Adversarial Networks—0
Gradient-Informed Quality Diversity for the Illumination of Discrete Spaces—0
Gradient-Guided Conditional Diffusion Models for Private Image Reconstruction: Analyzing Adversarial Impacts of Differential Privacy and Denoising—0
Deep D-bar: Real time Electrical Impedance Tomography Imaging with Deep Neural Networks—0
Bias in Large Language Models Across Clinical Applications: A Systematic Review—0
An Empirical Study of Batch Normalization and Group Normalization in Conditional Computation—0
HiFi Tuner: High-Fidelity Subject-Driven Fine-Tuning for Diffusion Models—0
Gradient-Free Textual Inversion—0
High-Fidelity Diffusion-based Image Editing—0
High-fidelity Endoscopic Image Synthesis by Utilizing Depth-guided Neural Surfaces—0
High-Fidelity Guided Image Synthesis with Latent Diffusion Models—0
Gradient-Free Classifier Guidance for Diffusion Model Sampling—0
High-Fidelity Image Generation With Fewer Labels—0
High-Fidelity Image Synthesis from Pulmonary Nodule Lesion Maps using Semantic Diffusion Model—0
Deep convolutional generative adversarial networks for traffic data imputation encoding time series as images—0
Deep Convolutional GANs for Car Image Generation—0
Gradient Domain Diffusion Models for Image Synthesis—0
Bias-Free FedGAN: A Federated Approach to Generate Bias-Free Datasets—0
3D Nephrographic Image Synthesis in CT Urography with the Diffusion Model and Swin Transformer—0
Deep Consensus Learning—0
MedUnifier: Unifying Vision-and-Language Pre-training on Medical Data with Vision Generation Task using Discrete Visual Representations—0
GPTDrawer: Enhancing Visual Synthesis through ChatGPT—0
Highly Personalized Text Embedding for Image Manipulation by Stable Diffusion—0
Deep Conditional HDRI: Inverse Tone Mapping via Dual Encoder-Decoder Conditioning Method—0
Improving Vision-and-Language Navigation by Generating Future-View Image Semantics—0
High Precision Score-based Diffusion Models—0
High Quality Diffusion Distillation on a Single GPU with Relative and Absolute Position Matching—0
Improving Visual Quality of Image Synthesis by A Token-based Generator with Transformers—0
In-Domain GAN Inversion for Faithful Reconstruction and Editability—0
High-resolution efficient image generation from WiFi CSI using a pretrained latent diffusion model—0
GPT-4V(ision) as a Generalist Evaluator for Vision-Language Tasks—0
Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models—0
GPT4Motion: Scripting Physical Motions in Text-to-Video Generation via Blender-Oriented GPT Planning—0
DeepCFL: Deep Contextual Features Learning from a Single Image—0
GPS as a Control Signal for Image Generation—0
High-resolution medical image synthesis using progressively grown generative adversarial networks—0
Dehazing-NeRF: Neural Radiance Fields from Hazy Images—0
Deli-Fisher GAN: Stable and Efficient Image Generation With Structured Latent Generative Space—0
High Resolution Seismic Waveform Generation using Denoising Diffusion—0
Good Seed Makes a Good Crop: Discovering Secret Seeds in Text-to-Image Diffusion Models—0
High-Resolution UAV Image Generation for Sorghum Panicle Detection—0
Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model—0
Deep Boosting: Joint Feature Selection and Analysis Dictionary Learning in Hierarchy—0
Beyond Words: Advancing Long-Text Image Generation via Multimodal Autoregressive Models—0
Deep Algorithm Unrolling for Biomedical Imaging—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