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Technical Papers
Shape Sets and Trees
Friday, 30 November 11:00 - 13:00 | Peridot 201
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Active Co-Analysis of a Set of ShapesWe present a semi-supervised learning method for the co-analysis of sets of shapes. We show the effectiveness of this method as a means to quickly converge towards an error-free consistent part labeling. Yunhai Wang, Shenzhen Institutes of Advanced Technology |
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Co-Abstraction of Shape CollectionsWe present a co-abstraction method that takes as input a collection of shapes, and produces a mutually consistent and individually identity-preserving abstraction of each shape. We hierarchically generate a spectrum of abstractions for each model in a collection, and then compute the appropriate abstraction level for each model. Mehmet Ersin Yumer, Carnegie Mellon University |
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An Optimization Approach for Extracting and Encoding Consistent MapsWe introduce a novel approach that takes as input a sparse set of imperfect initial maps between a collection of shapes and outputs a compact data structure which implicitly encodes an improved set of maps between all pairs of shapes. Qi-xing Huang, Stanford University |
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Inverse Design of Urban Procedural ModelsWe propose a framework that enables adding intuitive high-level control to an existing urban procedural model. Users can specify arbitrary target indicators to control the modeling process, and our system discovers how to alter the parameters of the urban procedural model so as to produce the desired 3D output Carlos Vanegas, University of California, Berkeley |
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Capturing and Animating the Morphogenesis of Polygonal Tree ModelsGiven a static tree model we present a method to compute developmental stages that approximate the tree’s natural growth. Based on structural similarity, branches are added where pruning has been applied or branches have died off over time. Furthermore, the user can explore and edit all intermediate stages. Soeren Pirk, University of Konstanz |
Sponsored by ACMSIGGRAPH