@inproceedings{39c6524331064337bfbcb1a43e64270e,
title = "DeepKey: Towards End-to-End Physical Key Replication From a Single Photograph",
abstract = "This paper describes DeepKey, an end-to-end deep neural architecture capable of taking a digital RGB image of an {\textquoteleft}everyday{\textquoteright} scene containing a pin tumbler key (e.g. lying on a table or carpet) and fully automatically inferring a printable 3D key model. We report on the key detection performance and describe how candidates can be transformed into physical prints. We show an example opening a real-world lock. Our system is described in detail, providing a breakdown of all components including key detection, pose normalisation, bitting segmentation and 3D model inference. We provide an in-depth evaluation and conclude by reflecting on limitations, applications, potential security risks and societal impact. We contribute the DeepKey Datasets of 5,300+ images covering a few test keys with bounding boxes, pose and unaligned mask data.",
author = "Rory Smith and Tilo Burghardt",
year = "2019",
month = feb,
day = "14",
doi = "10.1007/978-3-030-12939-2_34",
language = "English",
isbn = "9783030129385",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer, Cham",
pages = "487--502",
editor = "Thomas Brox and Andr{\'e}s Bruhn and Mario Fritz",
booktitle = "Pattern Recognition",
address = "Switzerland",
note = "40th German Conference on Pattern Recognition, GCPR 2018 ; Conference date: 09-10-2018 Through 12-10-2018",
}