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Mathias Gehrig
Mathias Gehrig
PhD Student, University of Zurich
Verified email at ifi.uzh.ch - Homepage
Title
Cited by
Cited by
Year
Beauty and the beast: Optimal methods meet learning for drone racing
E Kaufmann, M Gehrig, P Foehn, R Ranftl, A Dosovitskiy, V Koltun, ...
2019 International Conference on Robotics and Automation (ICRA), 690-696, 2019
892019
Video to events: Recycling video datasets for event cameras
D Gehrig, M Gehrig, J Hidalgo-Carrió, D Scaramuzza
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
642020
Focus is all you need: Loss functions for event-based vision
G Gallego, M Gehrig, D Scaramuzza
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
602019
AlphaPilot: Autonomous Drone Racing
P Foehn, D Brescianini, E Kaufmann, T Cieslewski, M Gehrig, M Muglikar, ...
2020 Robotics: Science and Systems (RSS), 2020
542020
Visual place recognition with probabilistic voting
M Gehrig, E Stumm, T Hinzmann, R Siegwart
2017 IEEE International Conference on Robotics and Automation (ICRA), 3192-3199, 2017
382017
Towards low-latency high-bandwidth control of quadrotors using event cameras
RS Dimitrova, M Gehrig, D Brescianini, D Scaramuzza
2020 IEEE International Conference on Robotics and Automation (ICRA), 4294-4300, 2020
272020
DSEC: A Stereo Event Camera Dataset for Driving Scenarios
M Gehrig, W Aarents, D Gehrig, D Scaramuzza
IEEE Robotics and Automation Letters, 2021
252021
Event-Based Angular Velocity Regression with Spiking Networks
M Gehrig, SB Shrestha, D Mouritzen, D Scaramuzza
IEEE International Conference on Robotics and Automation (ICRA), 4195-4202, 2020
222020
Combining events and frames using recurrent asynchronous multimodal networks for monocular depth prediction
D Gehrig, M Rüegg, M Gehrig, J Hidalgo-Carrió, D Scaramuzza
IEEE Robotics and Automation Letters 6 (2), 2822-2829, 2021
172021
Time lens: Event-based video frame interpolation
S Tulyakov, D Gehrig, S Georgoulis, J Erbach, M Gehrig, Y Li, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
172021
E-RAFT: Dense optical flow from event cameras
M Gehrig, M Millhäusler, D Gehrig, D Scaramuzza
2021 International Conference on 3D Vision (3DV), 197-206, 2021
7*2021
How to Calibrate Your Event Camera
M Muglikar, M Gehrig, D Gehrig, D Scaramuzza
IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2021
22021
Dense Continuous-Time Optical Flow from Events and Frames
M Gehrig, M Muglikar, D Scaramuzza
arXiv preprint arXiv:2203.13674, 2022
2022
Bridging the Gap between Events and Frames through Unsupervised Domain Adaptation
N Messikommer, D Gehrig, M Gehrig, D Scaramuzza
IEEE Robotics and Automation Letters, 2022
2022
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