# ByeGlassesGAN: Identity Preserving Eyeglasses Removal for Face Images

arXiv: https://arxiv.org/abs/2008.11042 · HTML: https://mlsanity.com/paper/2008.11042/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Aug 2020.

## Built on by (most cited first, 10 of 10)

- [Portrait Eyeglasses and Shadow Removal by Leveraging 3D Synthetic Data](https://mlsanity.com/paper/2203.10474/) (2022)
- [Text-guided Eyeglasses Manipulation with Spatial Constraints](https://mlsanity.com/paper/2304.12539/) (2023)
- [Segmentation-Reconstruction-Guided Facial Image De-occlusion](https://mlsanity.com/paper/2112.08022/) (2021)
- [FaceOcc: A Diverse, High-quality Face Occlusion Dataset for Human Face Extraction](https://mlsanity.com/paper/2201.08425/) (2022)
- [A comprehensive survey on semantic facial attribute editing using generative adversarial networks](https://mlsanity.com/paper/2205.10587/) (2022)
- [Manipulating Vehicle 3D Shapes through Latent Space Editing](https://mlsanity.com/paper/2410.23931/) (2024)
- [Disentangling Racial Phenotypes: Fine-Grained Control of Race-related Facial Phenotype Characteristics](https://mlsanity.com/paper/2403.19897/) (2024)
- [V-LASIK: Consistent Glasses-Removal from Videos Using Synthetic Data](https://mlsanity.com/paper/2406.14510/) (2024)
- [On the Impact of Face Segmentation-Based Background Removal on Recognition and Morphing Attack Detection](https://mlsanity.com/paper/2604.20585/) (2026)
- [Unwarping the Lens: A Physics-Grounded Approach to Video Glasses Removal](https://mlsanity.com/paper/2608.20212/) (2026)

## Abstract (arXiv)

In this paper, we propose a novel image-to-image GAN framework for eyeglasses removal, called ByeGlassesGAN, which is used to automatically detect the position of eyeglasses and then remove them from face images. Our ByeGlassesGAN consists of an encoder, a face decoder, and a segmentation decoder. The encoder is responsible for extracting information from the source face image, and the face decoder utilizes this information to generate glasses-removed images. The segmentation decoder is included to predict the segmentation mask of eyeglasses and completed face region. The feature vectors generated by the segmentation decoder are shared with the face decoder, which facilitates better reconstruction results. Our experiments show that ByeGlassesGAN can provide visually appealing results in the eyeglasses-removed face images even for semi-transparent color eyeglasses or glasses with glare. Furthermore, we demonstrate significant improvement in face recognition accuracy for face images with glasses by applying our method as a pre-processing step in our face recognition experiment.