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[2] X. Chen, B. Mersch, L. Nunes, R. Marcuzzi, I. Vizzo, J. Behley, and C. Stachniss. Automatic Labeling to Generate Training Data for Online LiDAR-Based Moving Object Segmentation. IEEE Robotics and Automation Letters (RA-L), 7(3):6107--6114, 2022. [ bib | DOI | http ]
[3] X. Chen, T. Läbe, A. Milioto, T. Röhling, J. Behley, and C. Stachniss. OverlapNet: A Siamese Network for Computing LiDAR Scan Similarity with Applications to Loop Closing and Localization. Autonomous Robots, 46:61--81, 2022. [ bib | DOI | .pdf ]
[4] X. Chen, S. Li, B. Mersch, L. Wiesmann, J. Gall, J. Behley, and C. Stachniss. Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data. IEEE Robotics and Automation Letters (RA-L), 6:6529--6536, 2021. [ bib | DOI | .pdf ]
[5] J. Ma, J. Zhang, J. Xu, R. Ai, W. Gu, and X. Chen*. Overlaptransformer: An efficient and yaw-angle-invariant transformer network for lidar-based place recognition. IEEE Robotics and Automation Letters (RA-L), 7(3):6958--6965, 2022. [ bib | DOI | .pdf ]
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[8] T. Guadagnino, X. Chen, M. Sodano, J. Behley, G. Grisetti, and C. Stachniss. Fast Sparse LiDAR Odometry Using Self-Supervised Feature Selection on Intensity Images. IEEE Robotics and Automation Letters (RA-L), 2022. [ bib | .pdf ]
[9] B. Mersch, X. Chen, I. Vizzo, L. Nunes, J. Behley, and C. Stachniss. Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions. IEEE Robotics and Automation Letters (RA-L), 7(3):7503--7510, 2022. [ bib | DOI | .pdf ]
[10] H. Dong, X. Chen*, S. Särkkä, and C. Stachniss. Online pole segmentation on range images for long-term lidar localization in urban environments. Robotics and Autonomous Systems, page 104283, 2022. [ bib | DOI | .pdf ]
[11] M. Arora, L. Wiesmann, X. Chen*, and C. Stachniss. Static Map Generation from 3D LiDAR Point Clouds Exploiting Ground Segmentation. Robotics and Autonomous Systems (RAS), 2022. [ bib ]
[12] L. Nunes, R. Marcuzzi, X. Chen, J. Behley, and C. Stachniss. SegContrast: 3D Point Cloud Feature Representation Learning through Self-supervised Segment Discrimination. IEEE Robotics and Automation Letters (RA-L), 7(2):2116--2123, 2022. [ bib | DOI | .pdf ]
[13] C. Shi, X. Chen, K. Huang, J. Xiao, H. Lu, and C. Stachniss. Keypoint Matching for Point Cloud Registration using Multiplex Dynamic Graph Attention Networks. IEEE Robotics and Automation Letters (RA-L), 6:8221--8228, 2021. [ bib | DOI | .pdf ]
[14] S. Li, X. Chen, Y. Liu, D. Dai, C. Stachniss, and J. Gall. Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platform. IEEE Robotics and Automation Letters (RA-L), 7(2):738--745, 2022. [ bib | DOI | .pdf ]
[15] L. Wiesmann, A. Milioto, X. Chen, C. Stachniss, and J. Behley. Deep Compression for Dense Point Cloud Maps. IEEE Robotics and Automation Letters (RA-L), 6:2060--2067, 2021. [ bib | DOI | .pdf ]

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