Local feature extraction network with high correspondences for 3d point cloud registration
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-021-03055-1.pdf
Reference50 articles.
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2. Han L, Xu L, Bobkov D et al (2019) Real-time global registration for globally consistent rgb-d slam. IEEE Transactions on Robotics 35(2):498–508
3. Deschaud JE (2018) IMLS-SLAM: scan-to-model matching based on 3D data. In: IEEE international conference on robotics and automation. pp 2480-2485
4. Lu W, Zhou Y, Wan G, et al (2019) L3-net: Towards learning based lidar localization for autonomous driving. In: IEEE conference on computer vision and pattern recognition. pp 6389-6398
5. Newell A, Yang K, Deng J (2016) Stacked hourglass networks for human pose estimation. In: European conference on computer vision. pp 483-499
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