Mathias Gehrig
Mathias Gehrig
Verified email at ifi.uzh.ch
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
382019
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
182017
Focus is all you need: Loss functions for event-based vision
G Gallego, M Gehrig, D Scaramuzza
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
152019
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
22020
Towards low-latency high-bandwidth control of quadrotors using event cameras
RS Dimitrova, M Gehrig, D Brescianini, D Scaramuzza
arXiv preprint arXiv:1911.04553, 2019
22019
AlphaPilot: Autonomous Drone Racing
P Foehn, D Brescianini, E Kaufmann, T Cieslewski, M Gehrig, M Muglikar, ...
arXiv preprint arXiv:2005.12813, 2020
12020
Event-Based Angular Velocity Regression with Spiking Networks
M Gehrig, SB Shrestha, D Mouritzen, D Scaramuzza
arXiv preprint arXiv:2003.02790, 2020
12020
Video to Events: Bringing Modern Computer Vision Closer to Event Cameras
D Gehrig, M Gehrig, J Hidalgo-Carrió, D Scaramuzza
arXiv preprint arXiv:1912.03095, 2019
2019
Focus Is All You Need: Loss Functions For Event-based Vision—Supplementary Material—
G Gallego, M Gehrig, D Scaramuzza, A Notation
The system can't perform the operation now. Try again later.
Articles 1–9