Afshin Dehghan, Gilad Baruch, Zhuoyuan Chen, Yuri Feigin, Peter Fu, Thomas Gebauer, Daniel Kurz, Tal Dimry, Brandon Joffe, Arik Schwartz, Elad Shulman. ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data. In Joaquin Vanschoren, Sai Kit Yeung, editors, Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, NeurIPS Datasets and Benchmarks 2021, December 2021, virtual. 2021. [doi]
@inproceedings{DehghanBCFFGKDJ21,
title = {ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data},
author = {Afshin Dehghan and Gilad Baruch and Zhuoyuan Chen and Yuri Feigin and Peter Fu and Thomas Gebauer and Daniel Kurz and Tal Dimry and Brandon Joffe and Arik Schwartz and Elad Shulman},
year = {2021},
url = {https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/66f041e16a60928b05a7e228a89c3799-Abstract-round1.html},
researchr = {https://researchr.org/publication/DehghanBCFFGKDJ21},
cites = {0},
citedby = {0},
booktitle = {Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, NeurIPS Datasets and Benchmarks 2021, December 2021, virtual},
editor = {Joaquin Vanschoren and Sai Kit Yeung},
}