@phdthesis{chen2022phd, author = {Xieyuanli Chen}, title = {{LiDAR-Based Semantic Perception for Autonomous Vehicles}}, school = {University of Bonn}, year = 2022, month = sep, url = {https://hdl.handle.net/20.500.11811/10228}, urn = https://nbn-resolving.org/urn:nbn:de:hbz:5-67873 }
@article{chen2022ral, author = {\textbf{X. Chen} and B. Mersch and L. Nunes and R. Marcuzzi and I. Vizzo and J. Behley and C. Stachniss}, title = {{Automatic Labeling to Generate Training Data for Online LiDAR-Based Moving Object Segmentation}}, journal = {IEEE Robotics and Automation Letters (RA-L)}, year = 2022, volume = 7, number = 3, pages = {6107-6114}, url = {http://arxiv.org/pdf/2201.04501}, issn = {2377-3766}, doi = {10.1109/LRA.2022.3166544}, codeurl = {https://github.com/PRBonn/auto-mos} }
@article{chen2022auro, author = {\textbf{X. Chen} and T. L\"abe and A. Milioto and T. R\"ohling and J. Behley and C. Stachniss}, title = {{OverlapNet: A Siamese Network for Computing LiDAR Scan Similarity with Applications to Loop Closing and Localization}}, journal = {Autonomous Robots}, year = {2022}, doi = {10.1007/s10514-021-09999-0}, issn = {1573-7527}, volume = 46, pages = {61--81}, codeurl = {https://github.com/PRBonn/OverlapNet}, url = {http://www.ipb.uni-bonn.de/pdfs/chen2021auro.pdf} }
@article{chen2021ral, title = {{Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data}}, author = {\textbf{X. Chen} and S. Li and B. Mersch and L. Wiesmann and J. Gall and J. Behley and C. Stachniss}, year = {2021}, volume = 6, issue = 4, pages = {6529-6536}, journal = {IEEE Robotics and Automation Letters (RA-L)}, url = {http://www.ipb.uni-bonn.de/pdfs/chen2021ral-iros.pdf}, codeurl = {https://github.com/PRBonn/LiDAR-MOS}, videourl = {https://youtu.be/NHvsYhk4dhw}, doi = {10.1109/LRA.2021.3093567}, issn = {2377-3766} }
@article{ma2022ral, author = {J. Ma and J. Zhang and J. Xu and R. Ai and W. Gu and C. Stachniss and \textbf{X. Chen*}}, journal = {IEEE Robotics and Automation Letters (RA-L)}, title = {OverlapTransformer: An Efficient and Yaw-Angle-Invariant Transformer Network for LiDAR-Based Place Recognition}, year = {2022}, volume = {7}, number = {3}, pages = {6958-6965}, doi = {10.1109/LRA.2022.3178797}, url = {https://arxiv.org/pdf/2203.03397.pdf}, codeurl = {https://github.com/haomo-ai/OverlapTransformer} }
@article{ma2022tie, author = {J. Ma and \textbf{X. Chen} and J. Xu and G. Xiong}, title = {{SeqOT: Spatial-Temporal Transformer Networks for Place Recognition Using Sequential LiDAR Data}}, journal = {IEEE Trans.~on Industrial Electronics}, year = {2022} }
@article{nunes2022ral-3duis, author = {L. Nunes and \textbf{X. Chen*} and R. Marcuzzi and A. Osep and L. Leal-Taixé and C. Stachniss and Jens Behley}, title = {{Unsupervised Class-Agnostic Instance Segmentation of 3D LiDAR Data for Autonomous Vehicles}}, journal = {IEEE Robotics and Automation Letters (RA-L)}, url = {https://www.ipb.uni-bonn.de/pdfs/nunes2022ral-iros.pdf}, codeurl = {https://github.com/PRBonn/3DUIS}, doi = {10.1109/LRA.2022.3187872}, year = 2022 }
@article{guadagnino2022ral, author = {T. Guadagnino and \textbf{X. Chen} and M. Sodano and J. Behley and G. Grisetti and C. Stachniss}, title = {{Fast Sparse LiDAR Odometry Using Self-Supervised Feature Selection on Intensity Images}}, journal = {IEEE Robotics and Automation Letters (RA-L)}, year = {2022}, url = {https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/guadagnino2022ral-iros.pdf} }
@article{mersch2022ral, author = {B. Mersch and \textbf{X. Chen} and I. Vizzo and L. Nunes and J. Behley and C. Stachniss}, title = {{Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions}}, journal = {IEEE Robotics and Automation Letters (RA-L)}, year = 2022, url = {https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/mersch2022ral.pdf}, volume = {7}, number = {3}, pages = {7503--7510}, doi = {10.1109/LRA.2022.3183245}, codeurl = {https://github.com/PRBonn/4DMOS}, videourl = {https://youtu.be/5aWew6caPNQ} }
@article{dong2022jras, title = {Online pole segmentation on range images for long-term LiDAR localization in urban environments}, journal = {Robotics and Autonomous Systems}, pages = {104283}, year = {2022}, issn = {0921-8890}, doi = {https://doi.org/10.1016/j.robot.2022.104283}, author = {H. Dong and \textbf{X. Chen*} and S. S{\"a}rkk{\"a} and C. Stachniss}, codeurl = {https://github.com/PRBonn/pole-localization}, url = {https://arxiv.org/pdf/2208.07364.pdf} }
@article{arora2022jras, author = {M. Arora and L. Wiesmann and \textbf{X. Chen*} and C. Stachniss}, title = {{Static Map Generation from 3D LiDAR Point Clouds Exploiting Ground Segmentation}}, journal = {Robotics and Autonomous Systems (RAS)}, year = {2022} }
@article{nunes2022ral, author = {L. Nunes and R. Marcuzzi and \textbf{X. Chen} and J. Behley and C. Stachniss}, title = {{SegContrast: 3D Point Cloud Feature Representation Learning through Self-supervised Segment Discrimination}}, journal = {IEEE Robotics and Automation Letters (RA-L)}, year = 2022, doi = {10.1109/LRA.2022.3142440}, issn = {2377-3766}, volume = {7}, number = {2}, pages = {2116-2123}, url = {http://www.ipb.uni-bonn.de/pdfs/nunes2022ral-icra.pdf}, codeurl = {https://github.com/PRBonn/segcontrast} }
@article{shi2021ral, title = {{Keypoint Matching for Point Cloud Registration using Multiplex Dynamic Graph Attention Networks}}, author = {C. Shi and \textbf{X. Chen} and K. Huang and J. Xiao and H. Lu and C. Stachniss}, year = {2021}, journal = {IEEE Robotics and Automation Letters (RA-L)}, volume = 6, issue = 4, pages = {8221-8228}, url = {http://www.ipb.uni-bonn.de/pdfs/shi2021ral-iros.pdf}, codeurl = {https://github.com/chenghao-shi/MDGAT-matcher}, doi = {10.1109/LRA.2021.3097275}, issn = {2377-3766} }
@article{li2022ral, author = {S. Li and \textbf{X. Chen} and Y. Liu and D. Dai and C. Stachniss and J. Gall}, title = {{Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platform}}, journal = {IEEE Robotics and Automation Letters (RA-L)}, year = 2022, doi = {10.1109/LRA.2021.3132059}, issn = {2377-3766}, volume = 7, number = 2, pages = {738-745}, url = {https://www.ipb.uni-bonn.de/pdfs/li2022ral.pdf}, codeurl = {https://github.com/sj-li/MINet} }
@article{wiesmann2021ral, author = {L. Wiesmann and A. Milioto and \textbf{X. Chen} and C. Stachniss and J. Behley}, title = {{Deep Compression for Dense Point Cloud Maps}}, journal = {IEEE Robotics and Automation Letters (RA-L)}, volume = 6, issue = 2, pages = {2060-2067}, doi = {10.1109/LRA.2021.3059633}, year = 2021, url = {http://www.ipb.uni-bonn.de/pdfs/wiesmann2021ral.pdf}, codeurl = {https://github.com/PRBonn/deep-point-map-compression}, videourl = {https://youtu.be/fLl9lTlZrI0} }
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