| SuMa++: Efficient LiDAR-based Semantic SLAM X Chen, A Milioto, E Palazzolo, P Giguère, J Behley, C Stachniss IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019 | 525 | 2019 |
| OverlapNet: Loop closing for LiDAR-based SLAM X Chen, T Läbe, A Milioto, T Röhling, O Vysotska, A Haag, J Behley, ... Robotics: Science and Systems (RSS) 16 (009), 1-10, 2020 | 280 | 2020 |
| Moving object segmentation in 3D LiDAR data: A learning-based approach exploiting sequential data X Chen, S Li, B Mersch, L Wiesmann, J Gall, J Behley, C Stachniss IEEE Robotics and Automation Letters 6 (4), 6529-6536, 2021 | 211 | 2021 |
| Overlaptransformer: An efficient and yaw-angle-invariant transformer network for lidar-based place recognition J Ma, J Zhang, J Xu, R Ai, W Gu, X Chen IEEE Robotics and Automation Letters 7 (3), 6958-6965, 2022 | 158 | 2022 |
| Range image-based LiDAR localization for autonomous vehicles X Chen, I Vizzo, T Läbe, J Behley, C Stachniss 2021 IEEE International Conference on Robotics and Automation (ICRA), 5802-5808, 2021 | 152 | 2021 |
| OverlapNet: A siamese network for computing LiDAR scan similarity with applications to loop closing and localization X Chen, T Läbe, A Milioto, T Röhling, J Behley, C Stachniss Autonomous Robots, 1-21, 2022 | 121 | 2022 |
| Poisson surface reconstruction for LiDAR odometry and mapping I Vizzo, X Chen, N Chebrolu, J Behley, C Stachniss 2021 IEEE international conference on robotics and automation (ICRA), 5624-5630, 2021 | 106 | 2021 |
| Multi-scale interaction for real-time lidar data segmentation on an embedded platform S Li, X Chen, Y Liu, D Dai, C Stachniss, J Gall IEEE Robotics and Automation Letters 7 (2), 738-745, 2021 | 90 | 2021 |
| Deep compression for dense point cloud maps L Wiesmann, A Milioto, X Chen, C Stachniss, J Behley IEEE Robotics and Automation Letters 6 (2), 2060-2067, 2021 | 88 | 2021 |
| Automatic labeling to generate training data for online LiDAR-based moving object segmentation X Chen, B Mersch, L Nunes, R Marcuzzi, I Vizzo, J Behley, C Stachniss IEEE Robotics and Automation Letters 7 (3), 6107-6114, 2022 | 87 | 2022 |
| Segcontrast: 3d point cloud feature representation learning through self-supervised segment discrimination L Nunes, R Marcuzzi, X Chen, J Behley, C Stachniss IEEE Robotics and Automation Letters 7 (2), 2116-2123, 2022 | 83 | 2022 |
| Bow3d: Bag of words for real-time loop closing in 3d lidar slam Y Cui, X Chen, Y Zhang, J Dong, Q Wu, F Zhu IEEE Robotics and Automation Letters 8 (5), 2828-2835, 2022 | 75 | 2022 |
| Efficient spatial-temporal information fusion for lidar-based 3d moving object segmentation J Sun, Y Dai, X Zhang, J Xu, R Ai, W Gu, X Chen 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022 | 75 | 2022 |
| Receding moving object segmentation in 3d lidar data using sparse 4d convolutions B Mersch, X Chen, I Vizzo, L Nunes, J Behley, C Stachniss IEEE Robotics and Automation Letters 7 (3), 7503-7510, 2022 | 72 | 2022 |
| Robust SLAM system based on monocular vision and LiDAR for robotic urban search and rescue X Chen, H Zhang, H Lu, J Xiao, Q Qiu, Y Li 2017 IEEE International Symposium on Safety, Security and Rescue Robotics …, 2017 | 70 | 2017 |
| Keypoint matching for point cloud registration using multiplex dynamic graph attention networks C Shi, X Chen, K Huang, J Xiao, H Lu, C Stachniss IEEE Robotics and Automation Letters 6 (4), 8221-8228, 2021 | 60 | 2021 |
| A survey on global lidar localization: Challenges, advances and open problems H Yin, X Xu, S Lu, X Chen, R Xiong, S Shen, C Stachniss, Y Wang International Journal of Computer Vision, 1-33, 2024 | 58* | 2024 |
| Nerf-loam: Neural implicit representation for large-scale incremental lidar odometry and mapping J Deng, Q Wu, X Chen, S Xia, Z Sun, G Liu, W Yu, L Pei Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 58 | 2023 |
| Learning an Overlap-based Observation Model for 3D LiDAR Localization X Chen, T Läbe, L Nardi, J Behley, C Stachniss IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020 | 55 | 2020 |
| Self-supervised point cloud prediction using 3d spatio-temporal convolutional networks B Mersch, X Chen, J Behley, C Stachniss Conference on Robot Learning, 1444-1454, 2022 | 54 | 2022 |
Cyrill StachnissProfessor for Photogrammetry & Robotics, University of Bonn確認したメール アドレス: igg.uni-bonn.de