This page contains the front-end of LocNet network, implemented by Matlab.
For example, you can use the files in kitti_dataset/range to achieve the representations, based on the absolute range information. Specifically, the binsToImageCells.m is the main file to obtain the image-like cells.
We also present the comparative methods, please refer to the Comparisons.
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}
As for the caffe model in these papers, please refer to LocNet_caffe.
If you have any questions, please contact: Huan Yin zjuyinhuan@gmail.com.