Data to 7 Oct 2026

Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation

arXiv 2008.00951 ↗First posted 3 Aug 2020cs.CVcited by 727

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Cited by 106 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We present a generic image-to-image translation framework, pixel2style2pixel (pSp). Our pSp framework is based on a novel encoder network that directly generates a series of style vectors which are fed into a pretrained StyleGAN generator, forming the extended W+ latent space. We first show that our encoder can directly embed real images into W+, with no additional optimization. Next, we propose utilizing our encoder to directly solve image-to-image translation tasks, defining them as encoding problems from some input domain into the latent domain. By deviating from the standard invert first, edit later methodology used with previous StyleGAN encoders, our approach can handle a variety of tasks even when the input image is not represented in the StyleGAN domain. We show that solving translation tasks through StyleGAN significantly simplifies the training process, as no adversary is required, has better support for solving tasks without pixel-to-pixel correspondence, and inherently supports multi-modal synthesis via the resampling of styles. Finally, we demonstrate the potential of our framework on a variety of facial image-to-image translation tasks, even when compared to state-of-the-art solutions designed specifically for a single task, and further show that it can be extended beyond the human facial domain.

Key facts. Cited by 727 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Aug 2020.

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Citing papers per year: 2021: 96; 2022: 202; 2023: 225; 2024: 124; 2025: 64; 2026: 16.

727 papers.

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2022Generative Adversarial Networkscited by 5,603
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2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
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2021StyleCLIP: Text-Driven Manipulation of StyleGAN Imagerycited by 990
2021Blended Diffusion for Text-driven Editing of Natural Imagescited by 924
2022Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translationcited by 897

38 more

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2021Diffusion Autoencoders: Toward a Meaningful and Decodable Representationcited by 447
2021Pivotal Tuning for Latent-based Editing of Real Imagescited by 427
2023ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generationcited by 414
2021GAN Inversion: A Surveycited by 366
2023InstantBooth: Personalized Text-to-Image Generation without Test-Time Finetuningcited by 343
2022Text2LIVE: Text-Driven Layered Image and Video Editingcited by 312
2023Text-to-image Diffusion Models in Generative AI: A Surveycited by 264
2021ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinementcited by 248
2023P+: Extended Textual Conditioning in Text-to-Image Generationcited by 242
2022Towards Robust Blind Face Restoration with Codebook Lookup Transformercited by 230
2023Break-A-Scene: Extracting Multiple Concepts from a Single Imagecited by 230
2021Advancing High-Resolution Video-Language Representation with Large-Scale Video Transcriptionscited by 226
2021HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editingcited by 208
2023Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Modelscited by 203
2021GAN Prior Embedded Network for Blind Face Restoration in the Wildcited by 197
2021High-Fidelity GAN Inversion for Image Attribute Editingcited by 197
2023TF-ICON: Diffusion-Based Training-Free Cross-Domain Image Compositioncited by 182
2022Sketch-Guided Text-to-Image Diffusion Modelscited by 180
2022StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGANcited by 169
2021StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generatorscited by 164
2023SceneScape: Text-Driven Consistent Scene Generationcited by 160
2021EditGAN: High-Precision Semantic Image Editingcited by 156
2023Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Modelscited by 156
2024PuLID: Pure and Lightning ID Customization via Contrastive Alignmentcited by 143
2021Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalizationcited by 141
2023Zero-Shot Video Editing Using Off-The-Shelf Image Diffusion Modelscited by 135
2024ReNoise: Real Image Inversion Through Iterative Noisingcited by 127
2022NeRF-Art: Text-Driven Neural Radiance Fields Stylizationcited by 126
2023Generalizing Dataset Distillation via Deep Generative Priorcited by 125
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2023Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervisioncited by 112
2024Stable Flow: Vital Layers for Training-Free Image Editingcited by 111
2023Ambient Diffusion: Learning Clean Distributions from Corrupted Datacited by 108

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