Data-driven suggestions for creativity support in 3D modeling

Author:

Chaudhuri Siddhartha1,Koltun Vladlen1

Affiliation:

1. Stanford University

Abstract

We introduce data-driven suggestions for 3D modeling. Data-driven suggestions support open-ended stages in the 3D modeling process, when the appearance of the desired model is ill-defined and the artist can benefit from customized examples that stimulate creativity. Our approach computes and presents components that can be added to the artist's current shape. We describe shape retrieval and shape correspondence techniques that support the generation of data-driven suggestions, and report preliminary experiments with a tool for creative prototyping of 3D models.

Funder

Division of Computing and Communication Foundations

Division of Social and Economic Sciences

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design

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