We present SceneSuggest: an interactive 3D scene design system providing context-driven suggestions for 3D model retrieval and placement. Using a point-and-click metaphor we specify regions in a scene in which to automatically place and orient relevant 3D models. Candidate models are ranked using a set of static support, position, and orientation priors learned from 3D scenes. We show that our suggestions enable rapid assembly of indoor scenes. We perform a user study comparing suggestions to manual search and selection, as well as to suggestions with no automatic orientation. We find that suggestions reduce total modeling time by 32%, that orientation priors reduce time spent re-orienting objects by 27%, and that context-driven suggestions reduce the number of text queries by 50%.
@article{arxiv.1703.00061,
title = {SceneSuggest: Context-driven 3D Scene Design},
author = {Manolis Savva and Angel X. Chang and Maneesh Agrawala},
journal= {arXiv preprint arXiv:1703.00061},
year = {2017}
}