Mathias Gehrig

Mathias Gehrig

Universität Zürich

H-index: 14

Europe-Switzerland

About Mathias Gehrig

Mathias Gehrig, With an exceptional h-index of 14 and a recent h-index of 14 (since 2020), a distinguished researcher at Universität Zürich, specializes in the field of Robotics, Computer Vision, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

State Space Models for Event Cameras

Dense Continuous-Time Optical Flow from Event Cameras

Revisiting Token Pruning for Object Detection and Instance Segmentation

LEOD: Label-Efficient Object Detection for Event Cameras

From Chaos Comes Order: Ordering Event Representations for Object Detection

A Hybrid ANN-SNN Architecture for Low-Power and Low-Latency Visual Perception

Recurrent vision transformers for object detection with event cameras

Data-driven feature tracking for event cameras

Mathias Gehrig Information

University

Position

PhD Student

Citations(all)

1274

Citations(since 2020)

1260

Cited By

164

hIndex(all)

14

hIndex(since 2020)

14

i10Index(all)

14

i10Index(since 2020)

14

Email

University Profile Page

Google Scholar

Mathias Gehrig Skills & Research Interests

Robotics

Computer Vision

Machine Learning

Top articles of Mathias Gehrig

State Space Models for Event Cameras

arXiv preprint arXiv:2402.15584

2024/2/23

Mathias Gehrig
Mathias Gehrig

H-Index: 6

Davide Scaramuzza
Davide Scaramuzza

H-Index: 66

Dense Continuous-Time Optical Flow from Event Cameras

IEEE Transactions on Pattern Analysis and Machine Intelligence

2024/2/2

Revisiting Token Pruning for Object Detection and Instance Segmentation

2024

LEOD: Label-Efficient Object Detection for Event Cameras

arXiv preprint arXiv:2311.17286

2023/11/29

From Chaos Comes Order: Ordering Event Representations for Object Detection

2023/4/26

A Hybrid ANN-SNN Architecture for Low-Power and Low-Latency Visual Perception

arXiv preprint arXiv:2303.14176

2023/3/24

Recurrent vision transformers for object detection with event cameras

2023

Mathias Gehrig
Mathias Gehrig

H-Index: 6

Davide Scaramuzza
Davide Scaramuzza

H-Index: 66

Data-driven feature tracking for event cameras

2023/4/1

Bridging the gap between events and frames through unsupervised domain adaptation

IEEE Robotics and Automation Letters

2022/1/25

E-raft: Dense optical flow from event cameras

2021/11/1

DSEC: A Stereo Event Camera Dataset for Driving Scenarios

IEEE Robotics and Automation Letters

2021/3/25

Combining events and frames using recurrent asynchronous multimodal networks for monocular depth prediction

IEEE Robotics and Automation Letters

2021/2/19

How to Calibrate Your Event Camera

2021/4/27

Video to events: Recycling video datasets for event cameras

2020

Event-Based Angular Velocity Regression with Spiking Networks

2020

Mathias Gehrig
Mathias Gehrig

H-Index: 6

Davide Scaramuzza
Davide Scaramuzza

H-Index: 66

Towards low-latency high-bandwidth control of quadrotors using event cameras

2020/5/31

Mathias Gehrig
Mathias Gehrig

H-Index: 6

Davide Scaramuzza
Davide Scaramuzza

H-Index: 66

See List of Professors in Mathias Gehrig University(Universität Zürich)

Co-Authors

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