eprintid: 10130167
rev_number: 15
eprint_status: archive
userid: 608
dir: disk0/10/13/01/67
datestamp: 2021-06-25 11:05:59
lastmod: 2022-06-05 06:10:21
status_changed: 2021-06-25 11:05:59
type: article
metadata_visibility: show
creators_name: Zhang, M
creators_name: Wang, T
creators_name: Ceylan, D
creators_name: Mitra, NJ
title: Deep Detail Enhancement for Any Garment
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F48
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: Creating fine garment details requires significant efforts and huge computational resources. In contrast, a coarse shape may be easy to acquire in many scenarios (e.g., via low-resolution physically-based simulation, linear blend skinning driven by skeletal motion, portable scanners). In this paper, we show how to enhance, in a data-driven manner, rich yet plausible details starting from a coarse garment geometry. Once the parameterization of the garment is given, we formulate the task as a style transfer problem over the space of associated normal maps. In order to facilitate generalization across garment types and character motions, we introduce a patch-based formulation, that produces high-resolution details by matching a Gram matrix based style loss, to hallucinate geometric details (i.e., wrinkle density and shape). We extensively evaluate our method on a variety of production scenarios and show that our method is simple, light-weight, efficient, and generalizes across underlying garment types, sewing patterns, and body motion. Project page: http://geometry.cs.ucl.ac.uk/projects/2021/DeepDetailEnhance/.
date: 2021-05-01
date_type: published
official_url: http://dx.doi.org/10.1111/cgf.142642
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1869246
doi: 10.1111/cgf.142642
lyricists_name: Mitra, Niloy
lyricists_name: Zhang, Meng
lyricists_id: NMITR19
lyricists_id: MZHAE12
actors_name: Zhang, Meng
actors_id: MZHAE12
actors_role: owner
full_text_status: public
publication: Computer Graphics Forum
volume: 40
number: 2
pagerange: 399-411
citation:        Zhang, M;    Wang, T;    Ceylan, D;    Mitra, NJ;      (2021)    Deep Detail Enhancement for Any Garment.                   Computer Graphics Forum , 40  (2)   pp. 399-411.    10.1111/cgf.142642 <https://doi.org/10.1111/cgf.142642>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10130167/1/paper_MengZephyr_DDE.pdf