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Tanks and temples: Benchmarking large-scale scene reconstruction

Cited 446 time in Web of Science Cited 692 time in Scopus
Authors

Knapitsch, Arno; Park, Jaesik; Zhou, Qian-Yi; Koltun, Vladlen

Issue Date
2017-07
Publisher
Association for Computing Machinary, Inc.
Citation
ACM Transactions on Graphics, Vol.36 No.4
Abstract
We present a benchmark for image-based 3D reconstruction. The benchmark sequences were acquired outside the lab, in realistic conditions. Ground-truth data was captured using an industrial laser scanner. The benchmark includes both outdoor scenes and indoor environments. High-resolution video sequences are provided as input, supporting the development of novel pipelines that take advantage of video input to increase reconstruction fidelity. We report the performance of many image-based 3D reconstruction pipelines on the new benchmark. The results point to exciting challenges and opportunities for future work.
ISSN
0730-0301
URI
https://hdl.handle.net/10371/201317
DOI
https://doi.org/10.1145/3072959.3073599
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  • College of Engineering
  • Dept. of Computer Science and Engineering
Research Area Computer Graphics, Computer Vision, Machine Learning, Robotics

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