Title
3D shape creation by style transfer
Abstract
In this paper, we propose a new style transfer method for automatic 3D shape creation based on new concepts of style and content of 3D shapes. Our unsupervised style transfer method could plausibly create novel shapes not only by recombining existent styles and contents in a set but also by combining new-coming styles or contents with the existent ones conveniently. This feature provides a better way to increase the diversity of created shapes. The process of shape creation can be summarized as two stages. First, style and content separation is performed to analyzed shapes in a set. Second, novel shapes are created by style transfer. In our setting, contents are first separated via clustering shapes using a new defined global shape distance, and then, style parts are clustered into different style classes. Specifically, style parts are extracted from each pair of intra-content shapes through comparing their multi-scale corresponding patches instead of corresponding parts. This strategy makes the process of extracting style parts become insensitive to slight geometric changes. The multi-scale corresponding patches are obtained via partitioning the two shapes in a consistent way by the proposed correspondence transfer. Meanwhile, to quantify the comparison results for locating style parts, a novel local shape difference function (LSDF) is introduced. Based on LSDF, extracting a style part from each shape is formulated as an optimal LSDF threshold selection problem. In the experiments, we test our method in several sets of man-made 3D shapes and obtain plausible created shapes based on the reasonably separated styles and contents.
Year
DOI
Venue
2015
10.1007/s00371-014-0999-1
The Visual Computer
Keywords
Field
DocType
Style and content separation, Style transfer, Shape creation, Local shape difference function
Computer vision,Computer science,3d shapes,Artificial intelligence,Cluster analysis,Shape analysis (digital geometry)
Journal
Volume
Issue
ISSN
31
9
1432-2315
Citations 
PageRank 
References 
4
0.41
27
Authors
4
Name
Order
Citations
PageRank
Han Zhizhong119818.28
Zhenbao Liu2934.33
Junwei Han33501194.57
Shuhui Bu437521.34