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Understanding the scene is key for autonomously navigating vehicles and the ability to segment the surroundings online into moving and non-moving objects is a central ingredient for this task.
The hungarian method for the assignment problem
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Laser-based Segment Classification Using a Mixture of Bag-of-Words
J. Behley, V. Steinhage, and A. Cremers · 2013
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Density-based clustering based on hierarchical density estimates
R.J. Campello, D. Moulavi, and J. Sander · 2013
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Vision meets Robotics: The KITTI Dataset
A. Geiger, P. Lenz, C. Stiller, and R. Urtasun · 2013
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Autonomous Robot Navigation in Highly Populated Pedestrian Zones
R. Kümmerle, M. Ruhnke, B. Steder, C. Stachniss, and W. Burgard · 2014
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Long-term 3d map maintenance in dynamic environments
F. Pomerleau, P. Krüsiand, F. Colas, P. Furgale, and R. Siegwart · 2014
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Hierarchical density estimates for data clustering, visualization, and outlier detection
R.J. Campello, D. Moulavi, A. Zimek, and J. Sander · 2015
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Street Environment Change Detection from Mobile Laser Scanning Point Clouds
W. Xiao, B. Vallet, M. Brédif, and N. Paparoditis · 2015
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Fast range image-based segmentation of sparse 3d laser scans for online operation
I. Bogoslavskyi and C. Stachniss · 2016
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Rigid scene flow for 3d lidar scans
A. Dewan, T. Caselitz, G.D. Tipaldi, and W. Burgard · 2016
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An approach to extract moving objects from mls data using a volumetric background representation
J. Gehrung, M. Hebel, M. Arens, and U. Stilla · 2017
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Efficient Surfel-Based SLAM using 3D Laser Range Data in Urban Environments
J. Behley and C. Stachniss · 2018
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The peopleremover—removing dynamic objects from 3-d point cloud data by traversing a voxel occupancy grid
J. Schauer and A. Nüchter · 2018
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SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences
J. Behley, M. Garbade, A. Milioto, J. Quenzel, S. Behnke, C. Stachniss, and J. Gall · 2019
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SuMa++: Efficient LiDAR-based Semantic SLAM
X. Chen, A. Milioto, E. Palazzolo, P. Giguère, J. Behley, and C. Stachniss · 2019
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FlowNet3D: Learning Scene Flow in 3D Point Clouds
X. Liu, C.R. Qi, and L.J. Guibas · 2019
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L3-Net: Towards Learning Based LiDAR Localization for Autonomous Driving
W. Lu, Y. Zhou, G. Wan, S. Hou, and S. Song · 2019
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RangeNet++: Fast and Accurate LiDAR Semantic Segmentation
A. Milioto, I. Vizzo, J. Behley, and C. Stachniss · 2019
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KPConv: Flexible and Deformable Convolution for Point Clouds
H. Thomas, C. Qi, J. Deschaud, B. Marcotegui, F. Goulette, and L. Guibas · 2019
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Mapless online detection of dynamic objects in 3d lidar
D. Yoon, T. Tang, and T. Barfoot · 2019
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SpSequenceNet: Semantic Segmentation Network on 4D Point Clouds
H. Shi, G. Lin, H. Wang, T.Y. Hung, and Z. Wang · 2020
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3d multi-object tracking: A baseline and new evaluation metrics
X. Weng, J. Wang, D. Held, and K. Kitani · 2020
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Mapping the Static Parts of Dynamic Scenes from 3D LiDAR Point Clouds Exploiting Ground Segmentation
M. Arora, L. Wiesmann, X. Chen, and C. Stachniss · 2021
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SLIM: Self-Supervised LiDAR Scene Flow and Motion Segmentation
S.A. Baur, D.J. Emmerichs, F. Moosmann, P. Pinggera, B. Ommer, and A. Geiger · 2021
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Towards 3D LiDAR-based semantic scene understanding of 3D point cloud sequences: The SemanticKITTI Dataset
J. Behley, M. Garbade, A. Milioto, J. Quenzel, S. Behnke, J. Gall, and C. Stachniss · 2021
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nuScenes: A Multimodal Dataset for Autonomous Driving
H. Caesar, V. Bankiti, A. Lang, S. Vora, V. Liong, Q. Xu, A. Krishnan, Y. Pan, G. Baldan, and O. Beijbom · 2020
Cited alongside, same era.
Learning an Overlap-based Observation Model for 3D LiDAR Localization
X. Chen, T. Läbe, L. Nardi, J. Behley, and C. Stachniss · 2020
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SalsaNext: Fast, Uncertainty-Aware Semantic Segmentation of LiDAR Point Clouds
T. Cortinhal, G. Tzelepis, and E.E. Aksoy · 2020
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Graph Moving Object Segmentation
J.H. Giraldo, S. Javed, and T. Bouwmans · 2020
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Mulran: Multimodal range dataset for urban place recognition
G. Kim, Y. Park, Y. Cho, J. Jeong, and A. Kim · 2020
Cited alongside, same era.
Remove, then Revert: Static Point cloud Map Construction using Multiresolution Range Images
G. Kim and A. Kim · 2020
Cited alongside, same era.
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, and C. Stachniss · 2021
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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, and C. Stachniss · 2021
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Weakly Supervised Learning of Rigid 3D Scene Flow
Z. Gojcic, O. Litany, A. Wieser, L.J. Guibas, and T. Birdal · 2021
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Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platform
S. Li, X. Chen, Y. Liu, D. Dai, C. Stachniss, and J. Gall · 2021
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KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D
Y. Liao, J. Xie, and A. Geiger · 2021
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ERASOR: Egocentric Ratio of Pseudo Occupancy-Based Dynamic Object Removal for Static 3D Point Cloud Map Building
H. Lim, S. Hwang, and H. Myung · 2021
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Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks
B. Mersch, X. Chen, J. Behley, and C. Stachniss · 2021
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Inferring Objectives in Continuous Dynamic Games from Noise-Corrupted Partial State Observations
L. Peters, D. Fridovich-Keil, V. Rubies-Royo, C.J. Tomlin, and C. Stachniss · 2021
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Dynamic Object Aware LiDAR SLAM based on Automatic Generation of Training Data
P. Pfreundschuh, H.F.C. Hendrikx, V. Reijgwart, R. Dubé, R. Siegwart, and A. Cramariuc · 2021
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