# Style Transfer for Anime Sketches with Enhanced Residual U-net and Auxiliary Classifier GAN

arXiv: https://arxiv.org/abs/1706.03319 · HTML: https://mlsanity.com/paper/1706.03319/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Jun 2017.

## Built on by (most cited first, 28 of 28)

- [Rethinking and Improving the Robustness of Image Style Transfer](https://mlsanity.com/paper/2104.05623/) (2021)
- [HumanEdit: A High-Quality Human-Rewarded Dataset for Instruction-based Image Editing](https://mlsanity.com/paper/2412.04280/) (2024)
- [Eliminating Gradient Conflict in Reference-based Line-Art Colorization](https://mlsanity.com/paper/2207.06095/) (2022)
- [ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images](https://mlsanity.com/paper/2406.14794/) (2024)
- [DAF:re: A Challenging, Crowd-Sourced, Large-Scale, Long-Tailed Dataset For Anime Character Recognition](https://mlsanity.com/paper/2101.08674/) (2021)
- [AnimeDiffusion: Anime Face Line Drawing Colorization via Diffusion Models](https://mlsanity.com/paper/2303.11137/) (2023)
- [Focusing on Persons: Colorizing Old Images Learning from Modern Historical Movies](https://mlsanity.com/paper/2108.06515/) (2021)
- [Weather-Magician: Reconstruction and Rendering Framework for 4D Weather Synthesis In Real Time](https://mlsanity.com/paper/2505.19919/) (2025)
- [AIComposer: Any Style and Content Image Composition via Feature Integration](https://mlsanity.com/paper/2507.20721/) (2025)
- [Improving Sketch Colorization using Adversarial Segmentation Consistency](https://mlsanity.com/paper/2301.08590/) (2023)
- [Adversarial Segmentation Loss for Sketch Colorization](https://mlsanity.com/paper/2102.06192/) (2021)
- [Evaluation of Correctness in Unsupervised Many-to-Many Image Translation](https://mlsanity.com/paper/2103.15727/) (2021)
- [CSHNet: A Novel Information Asymmetric Image Translation Method](https://mlsanity.com/paper/2501.10197/) (2025)
- [Multi-modal Visual Place Recognition in Dynamics-Invariant Perception Space](https://mlsanity.com/paper/2105.07800/) (2021)
- [XCI-Sketch: Extraction of Color Information from Images for Generation of Colored Outlines and Sketches](https://mlsanity.com/paper/2108.11554/) (2021)
- [ACE: Zero-Shot Image to Image Translation via Pretrained Auto-Contrastive-Encoder](https://mlsanity.com/paper/2302.11705/) (2023)
- [inkn'hue: Enhancing Manga Colorization from Multiple Priors with Alignment Multi-Encoder VAE](https://mlsanity.com/paper/2311.01804/) (2023)
- [Galaxy image simplification using Generative AI](https://mlsanity.com/paper/2507.11692/) (2025)
- [Semantic Image Fusion](https://mlsanity.com/paper/2110.06697/) (2021)
- [ParaColorizer: Realistic Image Colorization using Parallel Generative Networks](https://mlsanity.com/paper/2208.08295/) (2022)
- [Neural Artistic Style Transfer with Conditional Adversaria](https://mlsanity.com/paper/2302.03875/) (2023)
- [Regularization by Neural Style Transfer for MRI Field-Transfer Reconstruction with Limited Data](https://mlsanity.com/paper/2308.10968/) (2023)
- [Constraint Latent Space Matters: An Anti-anomalous Waveform Transformation Solution from Photoplethysmography to Arterial Blood Pressure](https://mlsanity.com/paper/2402.17780/) (2024)
- [Computer-aided Colorization State-of-the-science: A Survey](https://mlsanity.com/paper/2410.02288/) (2024)
- [ColorizeDiffusion v2: Enhancing Reference-based Sketch Colorization Through Separating Utilities](https://mlsanity.com/paper/2504.06895/) (2025)
- [Towards High-resolution and Disentangled Reference-based Sketch Colorization](https://mlsanity.com/paper/2603.05971/) (2026)
- [Amplifying the imaging power of digital sky surveys with space telescopes data and generative AI](https://mlsanity.com/paper/2608.20666/) (2026)
- [No Pixel Left Behind: Filling Gaps in Anime Colorization](https://mlsanity.com/paper/2609.00800/) (2026)

## Abstract (arXiv)

Recently, with the revolutionary neural style transferring methods, creditable paintings can be synthesized automatically from content images and style images. However, when it comes to the task of applying a painting's style to an anime sketch, these methods will just randomly colorize sketch lines as outputs and fail in the main task: specific style tranfer. In this paper, we integrated residual U-net to apply the style to the gray-scale sketch with auxiliary classifier generative adversarial network (AC-GAN). The whole process is automatic and fast, and the results are creditable in the quality of art style as well as colorization.