# Transforming the Latent Space of StyleGAN for Real Face Editing

arXiv: https://arxiv.org/abs/2105.14230 · HTML: https://mlsanity.com/paper/2105.14230/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 28 of its 40 references that are in the map.
- First posted on arXiv 29 May 2021.

## Builds on (most cited first, 28 of 28)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Analyzing and Improving the Image Quality of StyleGAN](https://mlsanity.com/paper/1912.04958/) (2019)
- [Conditional Generative Adversarial Nets](https://mlsanity.com/paper/1411.1784/) (2014)
- [Improved Precision and Recall Metric for Assessing Generative Models](https://mlsanity.com/paper/1904.06991/) (2019)
- [Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation](https://mlsanity.com/paper/2008.00951/) (2020)
- [Interpreting the Latent Space of GANs for Semantic Face Editing](https://mlsanity.com/paper/1907.10786/) (2019)
- [Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?](https://mlsanity.com/paper/1904.03189/) (2019)
- [GANSpace: Discovering Interpretable GAN Controls](https://mlsanity.com/paper/2004.02546/) (2020)
- [Designing an Encoder for StyleGAN Image Manipulation](https://mlsanity.com/paper/2102.02766/) (2021)
- [Reliable Fidelity and Diversity Metrics for Generative Models](https://mlsanity.com/paper/2002.09797/) (2020)
- [In-Domain GAN Inversion for Real Image Editing](https://mlsanity.com/paper/2004.00049/) (2020)
- [Closed-Form Factorization of Latent Semantics in GANs](https://mlsanity.com/paper/2007.06600/) (2020)
- [InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs](https://mlsanity.com/paper/2005.09635/) (2020)
- [GAN Inversion: A Survey](https://mlsanity.com/paper/2101.05278/) (2021)
- [Image2StyleGAN++: How to Edit the Embedded Images?](https://mlsanity.com/paper/1911.11544/) (2019)
- [StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows](https://mlsanity.com/paper/2008.02401/) (2020)
- [StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation](https://mlsanity.com/paper/2011.12799/) (2020)
- [StyleRig: Rigging StyleGAN for 3D Control over Portrait Images](https://mlsanity.com/paper/2004.00121/) (2020)
- [Editing in Style: Uncovering the Local Semantics of GANs](https://mlsanity.com/paper/2004.14367/) (2020)
- [GAN-Control: Explicitly Controllable GANs](https://mlsanity.com/paper/2101.02477/) (2021)
- [Improved StyleGAN Embedding: Where are the Good Latents?](https://mlsanity.com/paper/2012.09036/) (2020)
- [Collaborative Learning for Faster StyleGAN Embedding](https://mlsanity.com/paper/2007.01758/) (2020)
- [PIE: Portrait Image Embedding for Semantic Control](https://mlsanity.com/paper/2009.09485/) (2020)
- [GuidedStyle: Attribute Knowledge Guided Style Manipulation for Semantic Face Editing](https://mlsanity.com/paper/2012.11856/) (2020)
- [Style Intervention: How to Achieve Spatial Disentanglement with Style-based Generators?](https://mlsanity.com/paper/2011.09699/) (2020)

## Built on by (most cited first, 6 of 6)

- [StyleLight: HDR Panorama Generation for Lighting Estimation and Editing](https://mlsanity.com/paper/2207.14811/) (2022)
- [TransEditor: Transformer-Based Dual-Space GAN for Highly Controllable Facial Editing](https://mlsanity.com/paper/2203.17266/) (2022)
- [Face Generation and Editing with StyleGAN: A Survey](https://mlsanity.com/paper/2212.09102/) (2022)
- [One Model to Edit Them All: Free-Form Text-Driven Image Manipulation with Semantic Modulations](https://mlsanity.com/paper/2210.07883/) (2022)
- [Overparameterization Improves StyleGAN Inversion](https://mlsanity.com/paper/2205.06304/) (2022)
- [PS-StyleGAN: Illustrative Portrait Sketching using Attention-Based Style Adaptation](https://mlsanity.com/paper/2409.00345/) (2024)

## Abstract (arXiv)

Despite recent advances in semantic manipulation using StyleGAN, semantic editing of real faces remains challenging. The gap between the W space and the W+ space demands an undesirable trade-off between reconstruction quality and editing quality. To solve this problem, we propose to expand the latent space by replacing fully-connected layers in the StyleGAN's mapping network with attention-based transformers. This simple and effective technique integrates the aforementioned two spaces and transforms them into one new latent space called W++. Our modified StyleGAN maintains the state-of-the-art generation quality of the original StyleGAN with moderately better diversity. But more importantly, the proposed W++ space achieves superior performance in both reconstruction quality and editing quality. Despite these significant advantages, our W++ space supports existing inversion algorithms and editing methods with only negligible modifications thanks to its structural similarity with the W/W+ space. Extensive experiments on the FFHQ dataset prove that our proposed W++ space is evidently more preferable than the previous W/W+ space for real face editing. The code is publicly available for research purposes at https://github.com/AnonSubm2021/TransStyleGAN.