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 4751–4800 of 6689 papers

TitleStatusHype
Mindstorms in Natural Language-Based Societies of Mind—0
StyleHumanCLIP: Text-guided Garment Manipulation for StyleGAN-Human—0
Surrogate Modeling of Car Drag Coefficient with Depth and Normal Renderings—0
Stereotypes and Smut: The (Mis)representation of Non-cisgender Identities by Text-to-Image Models—0
Accurate generation of stochastic dynamics based on multi-model Generative Adversarial Networks—0
You Don't Have to Be Perfect to Be Amazing: Unveil the Utility of Synthetic Images—0
ZeroAvatar: Zero-shot 3D Avatar Generation from a Single Image—0
MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image GenerationCode0
Visual Programming for Text-to-Image Generation and Evaluation—0
Transferring Visual Attributes from Natural Language to Verified Image Generation—0
Optimal Linear Subspace Search: Learning to Construct Fast and High-Quality Schedulers for Diffusion ModelsCode0
BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editing—0
DuDGAN: Improving Class-Conditional GANs via Dual-Diffusion—0
SEEDS: Exponential SDE Solvers for Fast High-Quality Sampling from Diffusion ModelsCode0
Variational Bayesian Framework for Advanced Image Generation with Domain-Related Variables—0
Quantifying the effect of X-ray scattering for data generation in real-time defect detectionCode0
The CLIP Model is Secretly an Image-to-Prompt Converter—0
Design a Delicious Lunchbox in StyleCode0
InstructVid2Vid: Controllable Video Editing with Natural Language Instructions—0
iWarpGAN: Disentangling Identity and Style to Generate Synthetic Iris Images—0
DiffUCD:Unsupervised Hyperspectral Image Change Detection with Semantic Correlation Diffusion Model—0
DiffCap: Exploring Continuous Diffusion on Image Captioning—0
Constructing Dreams using Generative AI—0
Generative Sliced MMD Flows with Riesz KernelsCode0
Few-shot 3D Shape Generation—0
ReDirTrans: Latent-to-Latent Translation for Gaze and Head Redirection—0
Efficient Cross-Lingual Transfer for Chinese Stable Diffusion with Images as Pivots—0
SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models—0
Private Gradient Estimation is Useful for Generative Modeling—0
AIwriting: Relations Between Image Generation and Digital Writing—0
RoomDreamer: Text-Driven 3D Indoor Scene Synthesis with Coherent Geometry and Texture—0
Personalization as a Shortcut for Few-Shot Backdoor Attack against Text-to-Image Diffusion Models—0
Collaborative Generative AI: Integrating GPT-k for Efficient Editing in Text-to-Image Generation—0
Fusion-S2iGan: An Efficient and Effective Single-Stage Framework for Speech-to-Image Generation—0
Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models—0
Generative Adversarial Networks for Brain Images Synthesis: A Review—0
Wavelet-based Unsupervised Label-to-Image TranslationCode0
Towards Pragmatic Semantic Image Synthesis for Urban ScenesCode0
A Conditional Denoising Diffusion Probabilistic Model for Radio Interferometric Image ReconstructionCode0
The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)—0
Interactive Fashion Content Generation Using LLMs and Latent Diffusion Models—0
Parameter-Efficient Fine-Tuning for Medical Image Analysis: The Missed Opportunity—0
Beware of diffusion models for synthesizing medical images -- A comparison with GANs in terms of memorizing brain MRI and chest x-ray images—0
Learning the Visualness of Text Using Large Vision-Language Models—0
WeditGAN: Few-Shot Image Generation via Latent Space RelocationCode0
Generative Steganographic Flow—0
MMoT: Mixture-of-Modality-Tokens Transformer for Composed Multimodal Conditional Image Synthesis—0
Relightify: Relightable 3D Faces from a Single Image via Diffusion Models—0
Multi-Granularity Denoising and Bidirectional Alignment for Weakly Supervised Semantic SegmentationCode0
Real-World Denoising via Diffusion Model—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