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 6051–6100 of 6689 papers

TitleStatusHype
Fusion-S2iGan: An Efficient and Effective Single-Stage Framework for Speech-to-Image Generation—0
FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving—0
Text-to-Image Diffusion Models Cannot Count, and Prompt Refinement Cannot Help—0
FW-GAN: Flow-Navigated Warping GAN for Video Virtual Try-On—0
G2D2: Gradient-guided Discrete Diffusion for image inverse problem solving—0
G2PDiffusion: Genotype-to-Phenotype Prediction with Diffusion Models—0
G3FA: Geometry-guided GAN for Face Animation—0
GAFNet: A Global Fourier Self Attention Based Novel Network for multi-modal downstream tasks—0
GAGAN: Geometry-Aware Generative Adversarial Networks—0
GalaxyEdit: Large-Scale Image Editing Dataset with Enhanced Diffusion Adapter—0
BCAT: A Block Causal Transformer for PDE Foundation Models for Fluid Dynamics—0
GALOT: Generative Active Learning via Optimizable Zero-shot Text-to-image Generation—0
GameIR: A Large-Scale Synthesized Ground-Truth Dataset for Image Restoration over Gaming Content—0
Text-to-image Editing by Image Information Removal—0
GAN-Avatar: Controllable Personalized GAN-based Human Head Avatar—0
Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning—0
Bayesian Optimization for Controlled Image Editing via LLMs—0
Text-to-Image GAN with Pretrained Representations—0
GANORCON: Are Generative Models Useful for Few-shot Segmentation?—0
Text to Image Generation and Editing: A Survey—0
Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution—0
Text-to-Image Generation for Abstract Concepts—0
Text-to-Image Generation for Vocabulary Learning Using the Keyword Method—0
GANs for Medical Image Synthesis: An Empirical Study—0
A Novel Evaluation Framework for Image2Text Generation—0
Bayesian generative models can flag performance loss, bias, and out-of-distribution image content—0
Text to Image Generation: Leaving no Language Behind—0
GANTASTIC: GAN-based Transfer of Interpretable Directions for Disentangled Image Editing in Text-to-Image Diffusion Models—0
GAN with Skip Patch Discriminator for Biological Electron Microscopy Image Generation—0
Text-to-Image Generation Via Energy-Based CLIP—0
GarmentCrafter: Progressive Novel View Synthesis for Single-View 3D Garment Reconstruction and Editing—0
GaSpCT: Gaussian Splatting for Novel CT Projection View Synthesis—0
Text-to-Image Generation via Implicit Visual Guidance and Hypernetwork—0
Text-to-Image Generation with Attention Based Recurrent Neural Networks—0
Bayesian Conditional GAN for MRI Brain Image Synthesis—0
GaussiGAN: Controllable Image Synthesis with 3D Gaussians from Unposed Silhouettes—0
GazeCLIP: Towards Enhancing Gaze Estimation via Text Guidance—0
GazeFusion: Saliency-Guided Image Generation—0
GazeGAN - Unpaired Adversarial Image Generation for Gaze Estimation—0
GBSD: Generative Bokeh with Stage Diffusion—0
gCoRF: Generative Compositional Radiance Fields—0
EIUP: A Training-Free Approach to Erase Non-Compliant Concepts Conditioned on Implicit Unsafe Prompts—0
Gen2Det: Generate to Detect—0
BATINet: Background-Aware Text to Image Synthesis and Manipulation Network—0
BallGAN: 3D-aware Image Synthesis with a Spherical Background—0
GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editing—0
GenCO: Generating Diverse Designs with Combinatorial Constraints—0
Text-to-Image Synthesis: A Decade Survey—0
Text-to-Image Synthesis Based on Machine Generated Captions—0
Generalizable Object Keypoint Localization from Generative Priors—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