Publications
Y. Pan, X. Zhong, L. Wiesmann, T. Posewsky, J. Behley, and C. Stachniss
PIN-SLAM: LiDAR SLAM Using a Point-Based Implicit Neural Representation for Achieving
Global Map Consistency,
IEEE Transactions on Robotics (T-RO),
2024.
J. Weyler, F. Magistri, E. Marks, Y.L. Chong, M. Sodano, G. Roggiolani, N. Chebrolu, C.
Stachniss, and J. Behley
PhenoBench: A Large Dataset and Benchmarks for Semantic Image Interpretation in the
Agricultural Domain,
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI),
2024.
E.A. Marks, J. Bömer, F. Magistri, A. Sah, J. Behley, and C. Stachniss
BonnBeetClouds3D: A Dataset Towards Point Cloud-Based Organ-Level Phenotyping of Sugar Beet
Plants Under Real Field Conditions,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2024.
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,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2024.
Casado Herraez, D., L. Chang, M. Zeller, L. Wiesmann, J. Behley, M. Heidingsfeld, and C.
Stachniss
SPR: Single-Scan Radar Place Recognition,
IEEE Robotics & Automation Letters (RA-L),
2024.
F. Magistri, Y. Pan, J. Bartels, J. Behley, C. Stachniss, and C. Lehnert
Improving Robotic Fruit Harvesting Within Cluttered EnvironmentsThrough 3D Shape
Completion,
IEEE Robotics & Automation Letters (RA-L),
2024.
M. Sodano, F. Magistri, L. Nunes, J. Behley, and C. Stachniss
Open-World Semantic Segmentation Including Class Similarity,
Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
(CVPR),
2024.
L. Nunes, R. Marcuzzi, B. Mersch, J. Behley, and C. Stachniss
Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion,
Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
(CVPR),
2024.
X. Zhong, Y. Pan, C. Stachniss, and J. Behley
3D LiDAR Mapping in Dynamic Environments using a 4D Implicit Neural Representation,
Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
(CVPR),
2024.
M. Zeller, D. Cassado, J. Behley, M. Heidingsfeld, and C. Stachniss
Radar Tracker: Moving Instance Tracking in Sparse and Noisy Radar Point Clouds,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2024.
M.V.R. Malladi, T. Guadagnino, L. Lobefaro, M. Mattamala, H. Griess, J. Schweier, N.
Chebrolu, M. Fallon, J. Behley, and C. Stachniss
Tree Instance Segmentation and Traits Estimation for Forestry Environments Exploiting LiDAR
Data ,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2024.
F. Magistri, R. Marcuzzi, E.A. Marks, M. Sodano, J. Behley, and C. Stachniss
Efficient and Accurate Transformer-Based 3D Shape Completion and Reconstruction of Fruits
for Agricultural Robots,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2024.
M. Zeller, V. Sandhu, B. Mersch, J. Behley, M. Heidingsfeld, and C. Stachniss
Radar Instance Transformer: Reliable Moving Instance Segmentation in Sparse Radar Point
Clouds,
IEEE Transactions on Robotics (T-RO),
2024.
Y. Pan, X. Zhong, L. Wiesmann, T. Posewsky, J. Behley, and C. Stachniss
PIN-SLAM: LiDAR SLAM Using a Point-Based Implicit Neural Representation for Achieving
Global Map Consistency,
arXiv preprint,
vol. arXiv:2401.09101,
2024.
J. Weyler, T. Läbe, J. Behley, and C. Stachniss
Panoptic Segmentation with Partial Annotations for Agricultural Robots,
IEEE Robotics & Automation Letters (RA-L),
vol. 9(2), pp. 1660-1667,
2024.
R. Marcuzzi, L. Nunes, L. Wiesmann, E. Marks, J. Behley, and C. Stachniss
Mask4D: End-to-End Mask-Based 4D Panoptic Segmentation for LiDAR Sequences,
IEEE Robotics & Automation Letters (RA-L),
vol. 8(11), pp. 7487-7494,
2023.
G. Roggiolani, F. Magistri, T. Guadagnino, J. Behley, and C. Stachniss
Unsupervised Pre-Training for 3D Leaf Instance Segmentation,
IEEE Robotics & Automation Letters (RA-L),
vol. 8, pp. 7448-7455,
2023.
F. Magistri, J. Weyler, D. Gogoll, P. Lottes, J. Behley, N. Petrinic, and C.
Stachniss
From one Field to Another – Unsupervised Domain Adaptation for Semantic Segmentation in
Agricultural Robotics,
Computers and Electronics in Agriculture,
vol. 212, pp. 108114,
2023.
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 Robotics & Automation Letters (RA-L),
vol. 8(8), pp. 5180-5187,
2023.
Y.L. Chong, J. Weyler, P. Lottes, J. Behley, and C. Stachniss
Unsupervised Generation of Labeled Training Images for Crop-Weed Segmentation in New Fields
and on Different Robotic Platforms,
IEEE Robotics & Automation Letters (RA-L),
vol. 8(8), pp. 5259-5266,
2023.
Y. Pan, F. Magistri, T. Läbe, E. Marks, C. Smitt, C.S. McCool, J. Behley, and C.
Stachniss
Panoptic Mapping with Fruit Completion and Pose Estimation for Horticultural Robots,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2023.
N. Zimmerman, M. Sodano, E. Marks, J. Behley, and C. Stachniss
Constructing Metric-Semantic Maps using Floor Plan Priors for Long-Term Indoor
Localization,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2023.
J. Weyler, F. Magistri, E. Marks, Y. Chong, M. Roggiolani, N. Chebrolu, C. Stachniss, and
J. Behley
PhenoBench --- A Large Dataset and Benchmarks for Semantic Image Interpretationin the
Agricultural Domain,
arXiv preprint,
vol. arXiv:2306.04557,
2023.
L. Wiesmann, T. Guadagnino, I. Vizzo, N. Zimmerman, Y. Pan, H. Kuang, J. Behley, and C.
Stachniss
LocNDF: Neural Distance Field Mapping for Robot Localization,
IEEE Robotics & Automation Letters (RA-L),
vol. 8(8), pp. 4999-5006,
2023.
E. Marks, M. Sodano, F. Magistri, L. Wiesmann, D. Desai, R. Marcuzzi, J. Behley, and C.
Stachniss
High Precision Leaf Instance Segmentation in Point Clouds Obtained Under Real Field
Conditions,
IEEE Robotics & Automation Letters (RA-L),
vol. 8(8), pp. 4791-4798,
2023.
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,
Proc. of Robotics: Science and Systems (RSS),
2023.
J. Weyler, T. Läbe, F. Magistri, J. Behley, and C. Stachniss
Towards Domain Generalization in Crop and Weed Segmentation for Precision Farming
Robots,
IEEE Robotics & Automation Letters (RA-L),
vol. 8(6), pp. 3310-3317,
2023.
L. Nunes, L. Wiesmann, R. Marcuzzi, X. Chen, J. Behley, and C. Stachniss
Temporal Consistent 3D LiDAR Representation Learning for Semantic Perception in Autonomous
Driving,
Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
(CVPR),
2023.
H. Kuang, X. Chen, T. Guadagnino, N. Zimmerman, J. Behley, and C. Stachniss
IR-MCL: Implicit Representation-Based Online Global Localization,
IEEE Robotics & Automation Letters (RA-L),
vol. 8(3), pp. 1627-1634,
2023.
X. Zhong, Y. Pan, J. Behley, and C. Stachniss
SHINE-Mapping: Large-Scale 3D Mapping Using Sparse Hierarchical Implicit Neural
Representations,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2023.
M. Sodano, F. Magistri, T. Guadagnino, J. Behley, and C. Stachniss
Robust Double-Encoder Network for RGB-D Panoptic Segmentation,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2023.
A. Riccardi, S. Kelly, E. Marks, F. Magistri, T. Guadagnino, J. Behley, M. Bennewitz, and
C. Stachniss
Fruit Tracking Over Time Using High-Precision Point Clouds,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2023.
G. Roggiolani, M. Sodano, F. Magistri, T. Guadagnino, J. Behley, and C. Stachniss
Hierarchical Approach for Joint Semantic, Plant Instance, and Leaf Instance Segmentation in
the Agricultural Domain,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2023.
G. Roggiolani, F. Magistri, T. Guadagnino, J. Weyler, G. Grisetti, C. Stachniss, and J.
Behley
On Domain-Specific Pre-Training for Effective Semantic Perception in Agricultural
Robotics,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2023.
M. Zeller, V.S. Sandhu, B. Mersch, J. Behley, M. Heidingsfeld, and C. Stachniss
Radar Velocity Transformer: Single-scan Moving Object Segmentation in Noisy Radar Point
Clouds,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2023.
I. Vizzo, T. Guadagnino, B. Mersch, L. Wiesmann, J. Behley, and C. Stachniss
KISS-ICP: In Defense of Point-to-Point ICP -- Simple, Accurate, and Robust Registration If
Done the Right Way,
IEEE Robotics & Automation Letters (RA-L),
vol. 8(2), pp. 1-8,
2023.
R. Marcuzzi, L. Nunes, L. Wiesmann, J. Behley, and C. Stachniss
Mask-Based Panoptic LiDAR Segmentation for Autonomous Driving,
IEEE Robotics & Automation Letters (RA-L),
vol. 8(2), pp. 1141-1148,
2023.
L. Wiesmann, L. Nunes, J. Behley, and C. Stachniss
KPPR: Exploiting Momentum Contrast for Point Cloud-Based Place Recognition,
IEEE Robotics & Automation Letters (RA-L),
vol. 8(2), pp. 592-599,
2023.
Y. Wu, J. Kuang, X. Niu, J. Behley, L. Klingbeil, and H. Kuhlmann
Wheel-SLAM: Simultaneous Localization and Terrain Mapping Using One Wheel-mounted
IMU,
IEEE Robotics & Automation Letters (RA-L),
vol. 8(1), pp. 280-287,
2023.
M. Zeller, J. Behley, M. Heidingsfeld, and C. Stachniss
Gaussian Radar Transformer for Semantic Segmentation in Noisy Radar Data,
IEEE Robotics & Automation Letters (RA-L),
vol. 8(1), pp. 344-351,
2023.
N. Zimmerman, T. Guadagnino, X. Chen, J. Behley, and C. Stachniss
Long-Term Localization using Semantic Cues in Floor Plan Maps,
IEEE Robotics & Automation Letters (RA-L),
vol. 8(1), pp. 176-183,
2023.
H. Müller, N. Zimmerman, T. Polonelli, M. Magno, J. Behley, C. Stachniss, and L.
Benini
Fully On-board Low-Power Localization with Multizone Time-of-Flight Sensors on
Nano-UAVs,
Proc. of Design, Automation & Test in Europe Conference & Exhibition (DATE),
2023.
N. Zimmerman, L. Wiesmann, T. Guadagnino, T. Läbe, J. Behley, and C. Stachniss
Robust Onboard Localization in Changing Environments Exploiting Text Spotting,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2022.
F. Magistri, E. Marks, S. Nagulavancha, I. Vizzo, T. Läbe, J. Behley, M. Halstead, C.
McCool, and C. Stachniss
Contrastive 3D Shape Completion and Reconstruction for Agricultural Robots using RGB-D
Frames,
IEEE Robotics & Automation Letters (RA-L),
vol. 7(4), pp. 10120-10127,
2022.
I. Vizzo, B. Mersch, R. Marcuzzi, L. Wiesmann, J. Behley, and C. Stachniss
Make it Dense: Self-Supervised Geometric Scan Completion of Sparse 3D LiDAR Scans in Large
Outdoor Environments,
IEEE Robotics & Automation Letters (RA-L),
vol. 7(3), pp. 8534-8541,
2022.
L. Nunes, X. Chen, R. Marcuzzi, A. Osep, L. Leal-Taixé, C. Stachniss, and J. Behley
Unsupervised Class-Agnostic Instance Segmentation of 3D LiDAR Data for Autonomous
Vehicles,
IEEE Robotics & Automation Letters (RA-L),
2022.
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 & Automation Letters (RA-L),
vol. 7(3), pp. 7503-7510,
2022.
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 & Automation Letters (RA-L),
vol. 7(3), pp. 7597-7604,
2022.
L. Wiesmann, T. Guadagnino, I. Vizzo, G. Grisetti, J. Behley, and C. Stachniss
DCPCR: Deep Compressed Point Cloud Registration in Large-Scale Outdoor Environments,
IEEE Robotics & Automation Letters (RA-L),
vol. 7(3), pp. 6327-6334,
2022.
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 & Automation Letters (RA-L),
vol. 7(3), pp. 6107-6114,
2022.
I. Vizzo, T. Guadagnino, J. Behley, and C. Stachniss
VDBFusion: Flexible and Efficient TSDF Integration of Range Sensor Data,
Sensors,
vol. 22(3),
2022.
L. Wiesmann, R. Marcuzzi, C. Stachniss, and J. Behley
Retriever: Point Cloud Retrieval in Compressed 3D Maps,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2022.
J. Weyler, J. Quakernack, P. Lottes, J. Behley, and C. Stachniss
Joint Plant and Leaf Instance Segmentation on Field-Scale UAV Imagery,
IEEE Robotics & Automation Letters (RA-L),
vol. 7(2), pp. 3787-3794,
2022.
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 & Automation Letters (RA-L),
vol. 7(2), pp. 2116-2123,
2022.
R. Marcuzzi, L. Nunes, L. Wiesmann, I. Vizzo, J. Behley, and C. Stachniss
Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR
Scans,
IEEE Robotics & Automation Letters (RA-L),
vol. 7(2), pp. 1550-1557,
2022.
J. Weyler, F. Magistri, P. Seitz, J. Behley, and C. Stachniss
In-Field Phenotyping Based on Crop Leaf and Plant Instance Segmentation,
Proc. of the IEEE/CVF Winter Conference on Applications of Computer Vision
(WACV),
2022.
B. Mersch, X. Chen, J. Behley, and C. Stachniss
Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional
Networks,
Proc. of the Conference on Robot Learning (CoRL),
2021.
J. Behley, M. Garbade, A. Milioto, J. Quenzel, S. Behnke, J. Gall, and C. Stachniss
Towards 3D LiDAR-based semantic scene understanding of 3D point cloud sequences: The
SemanticKITTI Dataset,
International Journal on Robotics Research (IJRR),
vol. 40(8-9), pp. 959-967,
2021.
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,
vol. 46, pp. 61-81,
2021.
P. Rottmann, T. Posewsky, A. Milioto, C. Stachniss, and J. Behley
Improving Monocular Depth Estimation by Semantic Pre-training,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2021.
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 & Automation Letters (RA-L),
vol. 6, pp. 6529-6536,
2021.
M. Aygun, A. Osep, M. Weber, M. Maximov, C. Stachniss, J. Behley, and L.
Leal-Taixe
4D Panoptic Segmentation,
Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
(CVPR),
2021.
F. Magistri, N. Chebrolu, J. Behley, and C. Stachniss
Towards In-Field Phenotyping Exploiting Differentiable Rendering with Self-Consistency
Loss,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2021.
I. Vizzo, X. Chen, N. Chebrolu, J. Behley, and C. Stachniss
Poisson Surface Reconstruction for LiDAR Odometry and Mapping,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2021.
X. Chen, I. Vizzo, T. Läbe, J. Behley, and C. Stachniss
Range Image-based LiDAR Localization for Autonomous Vehicles,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2021.
J. Behley, A. Milioto, and C. Stachniss
A Benchmark for LiDAR-based Panoptic Segmentation based on KITTI,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2021.
N. Chebrolu, T. Läbe, O. Vysotska, J. Behley, and C. Stachniss
Adaptive Robust Kernels for Non-Linear Least Squares Problems,
IEEE Robotics & Automation Letters (RA-L),
vol. 6, pp. 2240-2247,
2021.
J. Weyler, A. Milioto, T. Falck, J. Behley, and C. Stachniss
Joint Plant Instance Detection and Leaf Count Estimation for In-Field Plant
Phenotyping,
IEEE Robotics & Automation Letters (RA-L),
vol. 6, pp. 3599-3606,
2021.
L. Wiesmann, A. Milioto, X. Chen, C. Stachniss, and J. Behley
Deep Compression for Dense Point Cloud Maps,
IEEE Robotics & Automation Letters (RA-L),
vol. 6, pp. 2060-2067,
2021.
A. Milioto, J. Behley, C. McCool, and C. Stachniss
LiDAR Panoptic Segmentation for Autonomous Driving,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2020.
X. Chen, T. Läbe, L. Nardi, J. Behley, and C. Stachniss
Learning an Overlap-based Observation Model for 3D LiDAR Localization,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2020.
F. Langer, A. Milioto, A. Haag, J. Behley, and C. Stachniss
Domain Transfer for Semantic Segmentation of LiDAR Data using Deep Neural Networks,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2020.
X. Chen, T. Läbe, A. Milioto, T. Röhling, O. Vysotska, A. Haag, J. Behley, and C.
Stachniss
OverlapNet: Loop Closing for LiDAR-based SLAM,
Proc. of Robotics: Science and Systems (RSS),
2020.
N. Chebrolu, T. Laebe, O. Vysotska, J. Behley, and C. Stachniss
Adaptive Robust Kernels for Non-Linear Least Squares Problems,
arXiv preprint,
2020.
J. Behley, A. Milioto, and C. Stachniss
A Benchmark for LiDAR-based Panoptic Segmentation based on KITTI,
arXiv preprint,
2020.
P. Lottes, J. Behley, N. Chebrolu, A. Milioto, and C. Stachniss
Robust joint stem detection and crop-weed classification using image sequences for
plant-specific treatment in precision farming,
Journal of Field Robotics (JFR),
vol. 37, pp. 20-34,
2020.
J. Behley, M. Garbade, A. Milioto, J. Quenzel, S. Behnke, C. Stachniss, and J. Gall
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences,
Proc. of the IEEE/CVF International Conference on Computer Vision (ICCV),
2019.
E. Palazzolo, J. Behley, P. Lottes, P. Giguere, and C. Stachniss
ReFusion: 3D Reconstruction in Dynamic Environments for RGB-D Cameras Exploiting
Residuals,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2019.
X. Chen, A. Milioto, E. Palazzolo, P. Giguère, J. Behley, and C. Stachniss
SuMa++: Efficient LiDAR-based Semantic SLAM,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2019.
A. Milioto, I. Vizzo, J. Behley, and C. Stachniss
RangeNet++: Fast and Accurate LiDAR Semantic Segmentation,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2019.
P. Lottes, J. Behley, A. Milioto, and C. Stachniss
Fully Convolutional Networks with Sequential Information for Robust Crop and Weed Detection
in Precision Farming,
IEEE Robotics & Automation Letters (RA-L),
vol. 3, pp. 3097-3104,
2018.
P. Lottes, J. Behley, N. Chebrolu, A. Milioto, and C. Stachniss
Joint Stem Detection and Crop-Weed Classification for Plant-specific Treatment in Precision
Farming,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2018.
J. Behley, and C. Stachniss
Efficient Surfel-Based SLAM using 3D Laser Range Data in Urban Environments,
Proc. of Robotics: Science and Systems (RSS),
2018.
J. Behley, V. Steinhage, and A.B. Cremers
Efficient Radius Neighbor Search in Three-dimensional Point Clouds,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2015.
J. Behley, V. Steinhage, and A.B. Cremers
Laser-based Segment Classification Using a Mixture of Bag-of-Words,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2013.
V. Steinhage, J. Behley, S. Meisel, and A.B. Cremers
Reconstruction by components for automated updating of 3D city models,
Applied Geomatrics,
vol. 5, pp. 285-298,
2013.
J. Behley, V. Steinhage, and A.B. Cremers
Performance of Histogram Descriptors for the Classification of 3D Laser Range Data in Urban
Environments,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2012.
F. Schöler, J. Behley, V. Steinhage, D. Schulz, and A.B. Cremers
Person Tracking in Three-Dimensional Laser Range Data with Explicit Occlusion
Adaption,
Proc. of the IEEE International Conference on Robotics and Automation (ICRA),
2011.
J. Behley, K. Kersting, D. Schulz, V. Steinhage, and A.B. Cremers
Learning to Hash Logistic Regression for Fast 3D Scan Point Classification,
Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS),
2010.
V. Steinhage, J. Behley, S. Meisel, and A. B. Cremers
Learning to Hash Logistic Regression for Fast 3D Scan Point Classification,
Proc. of the ISPRS-Workshop on Core Spatial Databases - Updating, Maintenance and
Services,
2010.
J. Behley, and V. Steinhage
Generation of 3D City Models Using Domain-Specific Information Fusion,
Proc. of the International Conference on Computer Vision Systems (ICVS),
2009.
V. Steinhage, J. Behley.
Model-Driven Generation of 3D City Models using Information Fusion on Aerial Imagery, Laser
Altimeter and Map Data,
GFaI-Workshop 3D-NordOst,
2008.
Teaching
Summer Term 24:
"Machine Learning for Robotics and Computer Vision" (Master)
Winter Term 23/24:
"Techniques for Self-Driving Cars" (Master) with Prof. Dr. Cyrill Stachniss and Benedikt
Mersch
Summer Term 23:
"Machine Learning for Robotics and Computer Vision" (Master)
Winter Term 22/23:
"Techniques for Self-Driving Cars" (Master) with Prof. Dr. Cyrill Stachniss and Benedikt
Mersch
Summer Term 22:
"Machine Learning for Robotics and Computer Vision" (Master)
Winter Term 21/22:
"Techniques for Self-Driving Cars" (Master) with Prof. Dr. Cyrill Stachniss, Lasse Peters,
and
Benedikt Mersch
Summer Term 21:
"Machine Learning for Robotics and Computer Vision" (Master)
Winter Term 20/21:
"Techniques for Self-Driving Cars" (Master) with Prof. Dr. Cyrill Stachniss, Nived Chebrolu,
and
Benedikt Mersch
Summer Term 15:
"Knowledge-based Image Understanding" (Master) together with PD Dr. Volker Steinhage and
Dominik
A. Klein
Summer Term 14:
"Knowledge-based Image Understanding" (Master) together with PD Dr. Volker Steinhage
Projectgroup "Intelligente Sehsystem" (Bachelor)
Summer Term 13:
Projectgroup "Intelligente Sehsystem" (Bachelor)
Summer Term 12:
Exercises "Autonomous Mobile Systems" (Master)
Winter Term 11/12:
Projectgroup "Intelligente Sehsystem" (Bachelor)
Summer Term 11:
Exercises "Autonomous Mobile Systems" (Master)
Winter Term 10/11:
Projectgroup "Intelligente Sehsysteme (Bachelor)
Summer Term 10
Exercises "Autonomous Mobile Systems" (Master)
Winter Term 09/10:
Projectgroup "Intelligente Sehsysteme" (Bachelor)