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Caffe models of network in LocNet

The implementation of LocNet back-end is based on caffe, and this page contains the caffe models of LocNet network.

In the models folder, for example, kitti_delta_range means that this model is used in KITTI dataset with Velodyne HDL-64E, with the Δ-r representations. The input of the network is the image-like representations of LiDAR data, which can be generated using LocNet_frontend.

If you use our code in an academic work, please cite the following paper:

@article{yin20193d,
  title={3D LiDAR-Based Global Localization Using Siamese Neural Network},
  author={Yin, Huan and Wang, Yue and Ding, Xiaqing and Tang, Li and Huang, Shoudong and Xiong, Rong},
  journal={IEEE Transactions on Intelligent Transportation Systems},
  year={2019},
  publisher={IEEE}
}

or other related conferences:

title={LocNet: Global localization in 3D point clouds for mobile vehicles}
title={Efficient 3D LIDAR based loop closing using deep neural network}