Sketch Beautification: Learning Part Beautification and Structure Refinement for Sketches of Man-made Objects

Deng Yu, Manfred Lau*, Lin Gao, Hongbo Fu*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

1 Citation (Scopus)
47 Downloads (CityUHK Scholars)

Abstract

We present a novel freehand sketch beautification method, which takes as input a freely drawn sketch of a man-made object and automatically beautifies it both geometrically and structurally. Beautifying a sketch is challenging because of its highly abstract and heavily diverse drawing manner. Existing methods are usually confined to their limited training samples and thus cannot beautify freely drawn sketches with both geometric and structural variations. To address this challenge, we adopt a divide-and-combine strategy. Specifically, we first parse an input sketch into semantic components, beautify individual components by a learned part beautification module based on part-level implicit manifolds, and then reassemble the beautified components through a structure beautification module. With this strategy, our method can go beyond the training samples and handle novel freehand sketches. We demonstrate the effectiveness of our system with extensive experiments and a perceptual study. © 2023 IEEE.
Original languageEnglish
Pages (from-to)6533-6546
JournalIEEE Transactions on Visualization and Computer Graphics
Volume30
Issue number9
Online published25 Dec 2023
DOIs
Publication statusPublished - Sept 2024

Funding

We thank the anonymous reviewers for their constructive comments. This work was partially supported by grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (No. CityU 11212119, 11206319, and 11205420), the Chow Sang Sang Group Research Fund/Donation, and the Centre for Applied Computing and Interactive Media (ACIM) of the School of Creative Media, CityU.

Research Keywords

  • sketch beautification
  • sketch implicit representation
  • sketch assembly

Publisher's Copyright Statement

  • COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Yu, D., Lau, M., Gao, L., & Fu, H. (2023). Sketch Beautification: Learning Part Beautification and Structure Refinement for Sketches of Man-made Objects. IEEE Transactions on Visualization and Computer Graphics. Advance online publication. https://doi.org/10.1109/TVCG.2023.3346995

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