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ORCIDMathias Gehrig
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2020 – today
- 2024
[j5]Mathias Gehrig
, Manasi Muglikar, Davide Scaramuzza:
Dense Continuous-Time Optical Flow From Event Cameras. IEEE Trans. Pattern Anal. Mach. Intell. 46(7): 4736-4746 (2024)- [c18]Asude Aydin, Mathias Gehrig, Daniel Gehrig, Davide Scaramuzza:
A Hybrid ANN-SNN Architecture for Low-Power and Low-Latency Visual Perception. CVPR Workshops 2024: 5701-5711 - [c17]Nikola Zubic, Mathias Gehrig, Davide Scaramuzza:
State Space Models for Event Cameras. CVPR 2024: 5819-5828 - [c16]Ziyi Wu, Mathias Gehrig, Qing Lyu, Xudong Liu, Igor Gilitschenski:
LEOD: Label-Efficient Object Detection for Event Cameras. CVPR 2024: 16933-16942 - [c15]Yifei Liu, Mathias Gehrig, Nico Messikommer, Marco Cannici, Davide Scaramuzza:
Revisiting Token Pruning for Object Detection and Instance Segmentation. WACV 2024: 2646-2656 - [i23]Nikola Zubic, Mathias Gehrig, Davide Scaramuzza:
State Space Models for Event Cameras. CoRR abs/2402.15584 (2024) - [i22]Nico Messikommer, Giovanni Cioffi, Mathias Gehrig, Davide Scaramuzza:
Reinforcement Learning Meets Visual Odometry. CoRR abs/2407.15626 (2024) - 2023
- [c14]Yannick Schnider, Stanislaw Wozniak, Mathias Gehrig, Jules Lecomte, Axel von Arnim, Luca Benini, Davide Scaramuzza, Angeliki Pantazi:
Neuromorphic Optical Flow and Real-time Implementation with Event Cameras. CVPR Workshops 2023: 4129-4138 - [c13]Nico Messikommer, Carter Fang, Mathias Gehrig, Davide Scaramuzza:
Data-Driven Feature Tracking for Event Cameras. CVPR 2023: 5642-5651 - [c12]Mathias Gehrig, Davide Scaramuzza:
Recurrent Vision Transformers for Object Detection with Event Cameras. CVPR 2023: 13884-13893 - [c11]Nikola Zubic, Daniel Gehrig, Mathias Gehrig, Davide Scaramuzza:
From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detection. ICCV 2023: 12800-12810 - [i21]Asude Aydin, Mathias Gehrig, Daniel Gehrig, Davide Scaramuzza:
A Hybrid ANN-SNN Architecture for Low-Power and Low-Latency Visual Perception. CoRR abs/2303.14176 (2023) - [i20]Yannick Schnider, Stanislaw Wozniak, Mathias Gehrig, Jules Lecomte, Axel von Arnim, Luca Benini, Davide Scaramuzza, Angeliki Pantazi:
Neuromorphic Optical Flow and Real-time Implementation with Event Cameras. CoRR abs/2304.07139 (2023) - [i19]Nikola Zubic, Daniel Gehrig, Mathias Gehrig, Davide Scaramuzza:
From Chaos Comes Order: Ordering Event Representations for Object Detection. CoRR abs/2304.13455 (2023) - [i18]Yifei Liu, Mathias Gehrig, Nico Messikommer, Marco Cannici, Davide Scaramuzza:
Revisiting Token Pruning for Object Detection and Instance Segmentation. CoRR abs/2306.07050 (2023) - [i17]Ziyi Wu, Mathias Gehrig, Qing Lyu, Xudong Liu, Igor Gilitschenski:
LEOD: Label-Efficient Object Detection for Event Cameras. CoRR abs/2311.17286 (2023) - 2022
- [j4]Philipp Foehn, Dario Brescianini, Elia Kaufmann, Titus Cieslewski, Mathias Gehrig, Manasi Muglikar, Davide Scaramuzza:
AlphaPilot: autonomous drone racing. Auton. Robots 46(1): 307-320 (2022) - [j3]Nico Messikommer, Daniel Gehrig, Mathias Gehrig, Davide Scaramuzza:
Bridging the Gap Between Events and Frames Through Unsupervised Domain Adaptation. IEEE Robotics Autom. Lett. 7(2): 3515-3522 (2022) - [i16]Mathias Gehrig, Manasi Muglikar, Davide Scaramuzza:
Dense Continuous-Time Optical Flow from Events and Frames. CoRR abs/2203.13674 (2022) - [i15]Nico Messikommer, Carter Fang, Mathias Gehrig, Davide Scaramuzza:
Data-driven Feature Tracking for Event Cameras. CoRR abs/2211.12826 (2022) - [i14]Mathias Gehrig, Davide Scaramuzza:
Recurrent Vision Transformers for Object Detection with Event Cameras. CoRR abs/2212.05598 (2022) - 2021
- [j2]Daniel Gehrig, Michelle Rüegg, Mathias Gehrig, Javier Hidalgo-Carrió, Davide Scaramuzza:
Combining Events and Frames Using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction. IEEE Robotics Autom. Lett. 6(2): 2822-2829 (2021) - [j1]Mathias Gehrig, Willem Aarents, Daniel Gehrig, Davide Scaramuzza:
DSEC: A Stereo Event Camera Dataset for Driving Scenarios. IEEE Robotics Autom. Lett. 6(3): 4947-4954 (2021) - [c10]Mathias Gehrig, Mario Millhäusler, Daniel Gehrig, Davide Scaramuzza:
E-RAFT: Dense Optical Flow from Event Cameras. 3DV 2021: 197-206 - [c9]Manasi Muglikar, Mathias Gehrig, Daniel Gehrig, Davide Scaramuzza:
How To Calibrate Your Event Camera. CVPR Workshops 2021: 1403-1409 - [c8]Stepan Tulyakov, Daniel Gehrig, Stamatios Georgoulis, Julius Erbach, Mathias Gehrig, Yuanyou Li, Davide Scaramuzza:
Time Lens: Event-Based Video Frame Interpolation. CVPR 2021: 16155-16164 - [i13]Daniel Gehrig, Michelle Rüegg, Mathias Gehrig, Javier Hidalgo-Carrió, Davide Scaramuzza:
Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction. CoRR abs/2102.09320 (2021) - [i12]Mathias Gehrig, Willem Aarents, Daniel Gehrig, Davide Scaramuzza:
DSEC: A Stereo Event Camera Dataset for Driving Scenarios. CoRR abs/2103.06011 (2021) - [i11]Manasi Muglikar, Mathias Gehrig, Daniel Gehrig, Davide Scaramuzza:
How to Calibrate Your Event Camera. CoRR abs/2105.12362 (2021) - [i10]Stepan Tulyakov, Daniel Gehrig, Stamatios Georgoulis, Julius Erbach, Mathias Gehrig, Yuanyou Li, Davide Scaramuzza:
TimeLens: Event-based Video Frame Interpolation. CoRR abs/2106.07286 (2021) - [i9]Mathias Gehrig, Mario Millhäusler, Daniel Gehrig, Davide Scaramuzza:
Dense Optical Flow from Event Cameras. CoRR abs/2108.10552 (2021) - [i8]Nico Messikommer, Daniel Gehrig, Mathias Gehrig, Davide Scaramuzza:
Bridging the Gap between Events and Frames through Unsupervised Domain Adaptation. CoRR abs/2109.02618 (2021) - 2020
- [c7]Daniel Gehrig, Mathias Gehrig, Javier Hidalgo-Carrió, Davide Scaramuzza:
Video to Events: Recycling Video Datasets for Event Cameras. CVPR 2020: 3583-3592 - [c6]Mathias Gehrig, Sumit Bam Shrestha, Daniel Mouritzen, Davide Scaramuzza:
Event-Based Angular Velocity Regression with Spiking Networks. ICRA 2020: 4195-4202 - [c5]Rika Sugimoto Dimitrova, Mathias Gehrig, Dario Brescianini, Davide Scaramuzza:
Towards Low-Latency High-Bandwidth Control of Quadrotors using Event Cameras. ICRA 2020: 4294-4300 - [c4]Philipp Foehn, Dario Brescianini, Elia Kaufmann, Titus Cieslewski, Mathias Gehrig, Manasi Muglikar, Davide Scaramuzza:
AlphaPilot: Autonomous Drone Racing. Robotics: Science and Systems 2020 - [i7]Mathias Gehrig, Sumit Bam Shrestha, Daniel Mouritzen, Davide Scaramuzza:
Event-Based Angular Velocity Regression with Spiking Networks. CoRR abs/2003.02790 (2020) - [i6]Philipp Foehn, Dario Brescianini, Elia Kaufmann, Titus Cieslewski, Mathias Gehrig, Manasi Muglikar, Davide Scaramuzza:
AlphaPilot: Autonomous Drone Racing. CoRR abs/2005.12813 (2020)
2010 – 2019
- 2019
- [c3]Guillermo Gallego, Mathias Gehrig, Davide Scaramuzza:
Focus Is All You Need: Loss Functions for Event-Based Vision. CVPR 2019: 12280-12289 - [c2]Elia Kaufmann, Mathias Gehrig, Philipp Foehn, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza:
Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing. ICRA 2019: 690-696 - [i5]Guillermo Gallego, Mathias Gehrig, Davide Scaramuzza:
Focus Is All You Need: Loss Functions For Event-based Vision. CoRR abs/1904.07235 (2019) - [i4]Rika Sugimoto Dimitrova, Mathias Gehrig, Dario Brescianini, Davide Scaramuzza:
Towards Low-Latency High-Bandwidth Control of Quadrotors using Event Cameras. CoRR abs/1911.04553 (2019) - [i3]Daniel Gehrig, Mathias Gehrig, Javier Hidalgo-Carrió, Davide Scaramuzza:
Video to Events: Bringing Modern Computer Vision Closer to Event Cameras. CoRR abs/1912.03095 (2019) - 2018
- [i2]Elia Kaufmann, Mathias Gehrig, Philipp Foehn, René Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza:
Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing. CoRR abs/1810.06224 (2018) - 2017
- [c1]Mathias Gehrig, Elena Stumm, Timo Hinzmann, Roland Siegwart:
Visual place recognition with probabilistic voting. ICRA 2017: 3192-3199 - 2016
- [i1]Mathias Gehrig, Elena Stumm, Timo Hinzmann, Roland Siegwart:
Visual Place Recognition with Probabilistic Vertex Voting. CoRR abs/1610.03548 (2016)
Coauthor Index
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last updated on 2024-10-11 18:20 CEST by the dblp team
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