Replica is a high-quality indoor scene 3D reconstruction dataset, containing 18 highly realistic indoor scenes. Each scene consists of a dense mesh, high-resolution high dynamic range (HDR) texture, glass and mirror surface information, semantic categories, and instance segmentation. The dataset is designed to support machine learning research that relies on visual, geometric, and semantic generative models.

Citation

@article{replica19arxiv, title = {The {R}eplica Dataset: A Digital Replica of Indoor Spaces}, author = {Julian Straub and Thomas Whelan and Lingni Ma and Yufan Chen and Erik Wijmans and Simon Green and Jakob J. Engel and Raul Mur-Artal and Carl Ren and Shobhit Verma and Anton Clarkson and Mingfei Yan and Brian Budge and Yajie Yan and Xiaqing Pan and June Yon and Yuyang Zou and Kimberly Leon and Nigel Carter and Jesus Briales and Tyler Gillingham and Elias Mueggler and Luis Pesqueira and Manolis Savva and Dhruv Batra and Hauke M. Strasdat and Renzo De Nardi and Michael Goesele and Steven Lovegrove and Richard Newcombe}, journal = {arXiv preprint arXiv:1906.05797}, year = {2019} }