Climaxing VR Character with Scene-Aware Aesthetic Dress Synthesis
Sifan Hou1 Yujia Wang1 Wei Liang1 Bing Ning2
1Beijing Institute of Technology
2Beijing Institute of Fashion Technology
Like real humans, virtual characters also need to dress up according to different application scenarios so that the
virtual character appears professionally, harmoniously, and naturally. However, manual selection is tedious, and
the appearances of virtual characters usually lack variety.
In this paper, we propose a new problem of synthesizing appropriate dress for a virtual character based on the
scenario analysis where he/she shows up. We come up with a pipeline to tackle the scenario-aware dress synthesis
problem. Firstly, given a scene, our approach predicts a dress code from the extracted high-level information
in the scene, consisting of season, occasion, and scene category. Then our approach tunes the dress details to
fit the aesthetic criteria and the virtual character's attributes. An optimization of a cost function implements
the tuning process. We carried out experiments to validate the efficacy of the proposed approach. The perceptual
study results show the good performance of our approach.
Digital Fashion, Visualization Design and Evaluation Methods, Fashion Outfit Generation.
Climaxing VR Character with Scene-Aware Aesthetic Dress Synthesis
Sifan Hou,
Yujia Wang,
Wei Liang
Bing Ning,
IEEE Virtual Reality Conference (IEEE VR 2021)
Paper
, Video
, Dataset (Coming Soon)
@inproceedings{ds2021hou,
title=
{Climaxing VR Character with Scene-Aware Aesthetic Dress Synthesis},
author = {Sifan, Hou and Wang, Yujia and Wei, Liang and Bing, Ning},
booktitle={IEEE Virtual Reality},
volume = {Coming soon},
number = {Coming soon},
year = {2021}
}
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