# End-to-End Rubbing Restoration Using Generative Adversarial Networks

arXiv: https://arxiv.org/abs/2205.03743 · HTML: https://mlsanity.com/paper/2205.03743/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 39 references that are in the map.
- First posted on arXiv 8 May 2022.

## Builds on (most cited first, 17 of 17)

- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022)
- [Image-to-Image Translation with Conditional Adversarial Networks](https://mlsanity.com/paper/1611.07004/) (2016)
- [Conditional Generative Adversarial Nets](https://mlsanity.com/paper/1411.1784/) (2014)
- [Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks](https://mlsanity.com/paper/1511.06434/) (2015)
- [A Neural Algorithm of Artistic Style](https://mlsanity.com/paper/1508.06576/) (2015)
- [Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks](https://mlsanity.com/paper/1604.04382/) (2016)
- [BEGAN: Boundary Equilibrium Generative Adversarial Networks](https://mlsanity.com/paper/1703.10717/) (2017)
- [Multi-Content GAN for Few-Shot Font Style Transfer](https://mlsanity.com/paper/1712.00516/) (2017)
- [High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis](https://mlsanity.com/paper/1611.09969/) (2016)
- [Image inpainting: A review](https://mlsanity.com/paper/1909.06399/) (2019)
- [Separating Style and Content for Generalized Style Transfer](https://mlsanity.com/paper/1711.06454/) (2017)
- [Auto-Encoder Guided GAN for Chinese Calligraphy Synthesis](https://mlsanity.com/paper/1706.08789/) (2017)
- [Learning to Write Stylized Chinese Characters by Reading a Handful of Examples](https://mlsanity.com/paper/1712.06424/) (2017)
- [Generating Handwritten Chinese Characters using CycleGAN](https://mlsanity.com/paper/1801.08624/) (2018)
- [Pyramid Embedded Generative Adversarial Network for Automated Font Generation](https://mlsanity.com/paper/1811.08106/) (2018)
- [Handwritten Chinese Font Generation with Collaborative Stroke Refinement](https://mlsanity.com/paper/1904.13268/) (2019)

## Abstract (arXiv)

Rubbing restorations are significant for preserving world cultural history. In this paper, we propose the RubbingGAN model for restoring incomplete rubbing characters. Specifically, we collect characters from the Zhang Menglong Bei and build up the first rubbing restoration dataset. We design the first generative adversarial network for rubbing restoration. Based on the dataset we collect, we apply the RubbingGAN to learn the Zhang Menglong Bei font style and restore the characters. The results of experiments show that RubbingGAN can repair both slightly and severely incomplete rubbing characters fast and effectively.