Conference and Journal Papers
Square Root Marginalization for Sliding-Window Bundle Adjustment
Nikolaus Demmel, David Schubert, Christiane Sommer, Daniel Cremers, Vladyslav Usenko
Proc. of the IEEE International Conf. on Computer Vision (ICCV), 2021
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Square Root Bundle Adjustment for Large-Scale Reconstruction
Nikolaus Demmel, Christiane Sommer, Daniel Cremers, Vladyslav Usenko
Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2021
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Efficient Derivative Computation for Cumulative B-Splines on Lie Groups(Oral Presentation)
Christiane Sommer, Vladyslav Usenko, David Schubert, Nikolaus Demmel, Daniel Cremers
Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2020
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Visual-Inertial Mapping With Non-Linear Factor Recovery
Vladyslav Usenko, Nikolaus Demmel, David Schubert, Jörg Stückler, Daniel Cremers
IEEE Robotics and Automation Letters (RA-L), 2020
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Rolling-Shutter Modelling for Direct Visual-Inertial Odometry
David Schubert, Nikolaus Demmel, Lukas von Stumberg, Vladyslav Usenko, Daniel Cremers
Proc. of the IEEE International Conference on Intelligent Robots and Systems (IROS), 2019
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Omnidirectional DSO: Direct Sparse Odometry With Fisheye Cameras
Hidenobu Matsuki, Lukas von Stumberg, Vladyslav Usenko, Jörg Stückler, Daniel Cremers
IEEE Robotics and Automation Letters (RA-L), 2018
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Direct Sparse Odometry with Rolling Shutter(Oral Presentation)
David Schubert, Nikolaus Demmel, Vladyslav Usenko, Jörg Stückler, Daniel Cremers
Proc. of the European Conf. on Computer Vision (ECCV), 2018
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The Double Sphere Camera Model
Vladyslav Usenko, Nikolaus Demmel, Daniel Cremers
Proc. of the International Conf. on 3D Vision (3DV), 2018
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The TUM VI Benchmark for Evaluating Visual-Inertial Odometry
David Schubert, Thore Goll, Nikolaus Demmel, Vladyslav Usenko, Jörg Stückler, Daniel Cremers
Proc. of the IEEE International Conference on Intelligent Robots and Systems (IROS), 2018
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Direct Sparse Visual-Inertial Odometry Using Dynamic Marginalization
Lukas von Stumberg, Vladyslav Usenko, Daniel Cremers
Proc. of the IEEE International Conference on Robotics and Automation (ICRA), 2018
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Real-time trajectory replanning for MAVs using uniform B-splines and a 3D circular buffer(Best Paper Award - Finalist)
Vladyslav Usenko, Lukas von Stumberg, Andrej Pangercic, Daniel Cremers
Proc. of the IEEE International Conference on Intelligent Robots and Systems (IROS), 2017
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From monocular SLAM to autonomous drone exploration
Lukas von Stumberg, Vladyslav Usenko, Jakob Engel, Jörg Stückler, Daniel Cremers
Proc. of the European Conference on Mobile Robots (ECMR), 2017
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Direct visual-inertial odometry with stereo cameras
Vladyslav Usenko, Jakob Engel, Jörg Stückler, Daniel Cremers
Proc. of the IEEE International Conference on Robotics and Automation (ICRA), 2016
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A Photometrically Calibrated Benchmark For Monocular Visual Odometry
Jakob Engel, Vladyslav Usenko, Daniel Cremers
arXiv.org, 2016
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Cloud-Based Collaborative 3D Mapping in Real-Time With Low-Cost Robots
Gajamohan Mohanarajah, Vladyslav Usenko, Mayank Singh, Raffaello D’Andrea, Markus Waibel
IEEE Transactions on Automation Science and Engineering, 2015
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Reconstructing Street-Scenes in Real-Time from a Driving Car
Vladyslav Usenko, Jakob Engel, Jörg Stückler, Daniel Cremers
Proc. of the International Conf. on 3D Vision (3DV), 2015
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Furniture Classification using WWW CAD Models
Vladyslav Usenko, Florian Seidel, Zoltán-Csaba Márton, Dejan Pangercic, Michael Beetz
IROS Workshop on Active Semantic Perception, 2012
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Book Chapters
TUM Flyers: Vision---Based MAV Navigation for Systematic Inspection of Structures
Vladyslav Usenko, Lukas von Stumberg, Jörg Stückler, Daniel Cremers
Bringing Innovative Robotic Technologies from Research Labs to Industrial End-users: The Experience of the European Robotics Challenges, 2020
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A Review and Quantitative Evaluation of Direct Visual–Inertial Odometry
Lukas von Stumberg, Vladyslav Usenko, Daniel Cremers
Multimodal Scene Understanding, 2019
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PhD Thesis
Visual-Inertial Navigation for Autonomous Vehicles
Vladyslav Usenko
PhD thesis, Technische Universität München, 2019
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