3D Object Instance Re-Localization in Changing Indoor Environments (original) (raw)

Technical University of Munich Google
* Authors share senior authorship.

3R-Scan is a large scale, real-world dataset which contains multiple 3D snapshots of naturally changing indoor environments, designed for benchmarking emerging tasks such as long-term SLAM, scene change detection and object instance re-localization.

Paper

International Conference on Computer Vision (ICCV 2019)
Paper | arXiv

@inproceedings{Wald2019RIO, title={RIO: 3D Object Instance Re-Localization in Changing Indoor Environments}, author={Johanna Wald, Armen Avetisyan, Nassir Navab, Federico Tombari, Matthias Niessner}, journal={Proceedings IEEE International Conference on Computer Vision (ICCV)}, year={2019} }

Acknowledgment

We would like to thank the volunteers who helped with 3D scanning, all expert annotators, as well as Jürgen Sturm, Tom Funkhouser and Maciej Halber for fruitful discussions. This work was funded by the Bavarian State Ministry of Education, Science and the Arts in the framework of the Centre Digitisation.Bavaria (ZD.B), the ERC Starting Grant Scan2CAD (804724), TUM-IAS for the Rudolf Mößbauer Fellowship, and a Google Research and Faculty award.