# Improving Shape Deformation in Unsupervised Image-to-Image Translation

arXiv: https://arxiv.org/abs/1808.04325 · HTML: https://mlsanity.com/paper/1808.04325/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Aug 2018.

## Built on by (most cited first, 19 of 19)

- [EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations](https://mlsanity.com/paper/2207.06635/) (2022)
- [Image-to-Image Translation: Methods and Applications](https://mlsanity.com/paper/2101.08629/) (2021)
- [DG-Font: Deformable Generative Networks for Unsupervised Font Generation](https://mlsanity.com/paper/2104.03064/) (2021)
- [AGTGAN: Unpaired Image Translation for Photographic Ancient Character Generation](https://mlsanity.com/paper/2303.07012/) (2023)
- [Coupling Model-Driven and Data-Driven Methods for Remote Sensing Image Restoration and Fusion](https://mlsanity.com/paper/2108.06073/) (2021)
- [USIS: Unsupervised Semantic Image Synthesis](https://mlsanity.com/paper/2109.14715/) (2021)
- [A Domain Gap Aware Generative Adversarial Network for Multi-domain Image Translation](https://mlsanity.com/paper/2110.10837/) (2021)
- [Collaborative Neural Rendering using Anime Character Sheets](https://mlsanity.com/paper/2207.05378/) (2022)
- [Leveraging generative adversarial networks to create realistic scanning transmission electron microscopy images](https://mlsanity.com/paper/2301.07743/) (2023)
- [Unpaired Image-to-Image Translation with Limited Data to Reveal Subtle Phenotypes](https://mlsanity.com/paper/2302.08503/) (2023)
- [DCL: Differential Contrastive Learning for Geometry-Aware Depth Synthesis](https://mlsanity.com/paper/2107.13087/) (2021)
- [FCR: Investigating Generative AI models for Forensic Craniofacial Reconstruction](https://mlsanity.com/paper/2508.18031/) (2025)
- [DGFont++: Robust Deformable Generative Networks for Unsupervised Font Generation](https://mlsanity.com/paper/2212.14742/) (2022)
- [Experiments on Anomaly Detection in Autonomous Driving by Forward-Backward Style Transfers](https://mlsanity.com/paper/2207.06055/) (2022)
- [Jurassic World Remake: Bringing Ancient Fossils Back to Life via Zero-Shot Long Image-to-Image Translation](https://mlsanity.com/paper/2308.07316/) (2023)
- [Human Machine Co-Creation. A Complementary Cognitive Approach to Creative Character Design Process Using GANs](https://mlsanity.com/paper/2311.13960/) (2023)
- [Few-Shot Unsupervised Image-to-Image Translation on complex scenes](https://mlsanity.com/paper/2106.03770/) (2021)
- [Exploring the Power of Generative Deep Learning for Image-to-Image Translation and MRI Reconstruction: A Cross-Domain Review](https://mlsanity.com/paper/2303.09012/) (2023)
- [Domain Adaptation for Image Classification of Defects in Semiconductor Manufacturing](https://mlsanity.com/paper/2506.15260/) (2025)

## Abstract (arXiv)

Unsupervised image-to-image translation techniques are able to map local texture between two domains, but they are typically unsuccessful when the domains require larger shape change. Inspired by semantic segmentation, we introduce a discriminator with dilated convolutions that is able to use information from across the entire image to train a more context-aware generator. This is coupled with a multi-scale perceptual loss that is better able to represent error in the underlying shape of objects. We demonstrate that this design is more capable of representing shape deformation in a challenging toy dataset, plus in complex mappings with significant dataset variation between humans, dolls, and anime faces, and between cats and dogs.