SceneSuggest: Context-driven 3D Scene Design

February 28, 2017 Β· Declared Dead Β· πŸ› arXiv.org

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Manolis Savva, Angel X. Chang, Maneesh Agrawala arXiv ID 1703.00061 Category cs.GR: Graphics Cross-listed cs.HC Citations 30 Venue arXiv.org Last Checked 2 months ago
Abstract
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%.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Graphics

R.I.P. πŸ‘» Ghosted

Everybody Dance Now

Caroline Chan, Shiry Ginosar, ... (+2 more)

cs.GR πŸ› ICCV πŸ“š 820 cites 7 years ago
R.I.P. πŸ‘» Ghosted

Animating Human Athletics

Jessica K. Hodgins, Wayne L. Wooten, ... (+2 more)

cs.GR πŸ› SIGGRAPH πŸ“š 765 cites 3 years ago

Died the same way β€” πŸ‘» Ghosted