All Relevant Papers

• 1.  Dataset

     • H. Lim, S. Jang, B. Mersch, J. Behley, H. Myung, and C. Stachniss, “HeLiMOS: A Dataset for moving object segmentation in 3D point clouds from heterogeneous LiDAR sensors,” in Proc. IEEE/RSJ Int. Conf. Intell. Robot. Syst., 2024 (Accepted. To Appear).

  2.  Static Map Building 

     • H. Lim, L. Nunes, B. Mersch, X. Chen, J. Behley, H. Myung, and C. Stachniss, “ERASOR2: Instance-aware robust 3D mapping of the static world in dynamic scenes,” in Robot. Sci. Syst., 2023, doi: https://doi.org/10.15607/rss.2023.xix.067.

     • H. Lim, S. Hwang, and H. Myung, “ERASOR: Egocentric ratio of pseudo occupancy-based dynamic object removal for static 3D point cloud map building,” IEEE Robot. Automat. Lett., vol. 6, no. 2, pp. 2272–2279, 2021.

  3. Moving Object Segmentation

     • S. Jang, M. Oh, B. Yu, I. Nahrendra, S. Lee, H. Lim, and H. Myung, “TOSS: Real-time tracking and moving object segmentation for static scene mapping,” in Proc. Int. Conf. Robot Intell. Tech. Appl., 2023, pp. 7255-7262.

     • B. Mersch, T. Guadagnino, X. Chen, I. Vizzo, J. Behley, and C. Stachniss, “Building volumetric beliefs for dynamic environments exploiting map-based moving object segmentation,” IEEE Robot. Automat. Lett., pp. 5180–5187, 2023.

     • 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 Robot. Automat. Lett., vol. 7, no. 3, pp. 7503–7510, 2022.

Copyright 

All point clouds are copyrighted by SNU RPM Labs, and MOS labels are copyrighted by KAIST Urban Robotics Lab. All the data are published under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License. You must attribute the work in the manner specified by the author. You may not use the work for commercial purposes, and you may only distribute the resulting work under the same license if you alter, transform, or create the work.