Style-content separation by anisotropic part scales
Kai Xu, Honghua Li, Hao Zhang, Daniel Cohen-Or, Yueshan Xiong, Zhi-Quan Cheng
In ACM Transactions on Graphics, 29(6), December 2010.
Abstract: We perform co-analysis of a set of man-made 3D objects to allow the creation of novel instances derived from the set. We analyze the objects at the part level and treat the anisotropic part scales as a shape style. The co-analysis then allows style transfer to synthesize new objects. The key to co-analysis is part correspondence, where a major challenge is the handling of large style variations and diverse geometric content in the shape set. We propose style-content separation as a means to address this challenge. Specifically, we define a correspondence-free style signature for style clustering. We show that confining analysis to within a style cluster facilitates tasks such as co-segmentation, content classification, and deformation-driven part correspondence. With part correspondence between each pair of shapes in the set, style transfer can be easily performed. We demonstrate our analysis and synthesis results on several sets of man-made objects with style and content variations.
Keyword(s): co-analysis, part correspondence, segmentation, shape analysis, style-content separation
@article{Xu:2010:SSB,
author = {Kai Xu and Honghua Li and Hao Zhang and Daniel Cohen-Or and Yueshan Xiong and Zhi-Quan Cheng},
title = {Style-content separation by anisotropic part scales},
journal = {ACM Transactions on Graphics},
volume = {29},
number = {6},
pages = {184:1--184:10},
month = dec,
year = {2010},
}
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