Daniel Gehrig

Orcid: 0000-0001-9952-3335

According to our database1, Daniel Gehrig authored at least 33 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2023
End-to-End Learned Event- and Image-based Visual Odometry.
CoRR, 2023

E-Calib: A Fast, Robust and Accurate Calibration Toolbox for Event Cameras.
CoRR, 2023

From Chaos Comes Order: Ordering Event Representations for Object Detection.
CoRR, 2023

A Hybrid ANN-SNN Architecture for Low-Power and Low-Latency Visual Perception.
CoRR, 2023

Event-based Agile Object Catching with a Quadrupedal Robot.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detection.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

A 5-Point Minimal Solver for Event Camera Relative Motion Estimation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Bridging the Gap Between Events and Frames Through Unsupervised Domain Adaptation.
IEEE Robotics Autom. Lett., 2022

Exploring Event Camera-Based Odometry for Planetary Robots.
IEEE Robotics Autom. Lett., 2022

Pushing the Limits of Asynchronous Graph-based Object Detection with Event Cameras.
CoRR, 2022

Time Lens++: Event-based Frame Interpolation with Parametric Non-linear Flow and Multi-scale Fusion.
CoRR, 2022

Are High-Resolution Event Cameras Really Needed?
CoRR, 2022

ESS: Learning Event-Based Semantic Segmentation from Still Images.
Proceedings of the Computer Vision - ECCV 2022, 2022

Time Lens++: Event-based Frame Interpolation with Parametric Nonlinear Flow and Multi-scale Fusion.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

AEGNN: Asynchronous Event-based Graph Neural Networks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Multi-Bracket High Dynamic Range Imaging with Event Cameras.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
Combining Events and Frames Using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction.
IEEE Robotics Autom. Lett., 2021

DSEC: A Stereo Event Camera Dataset for Driving Scenarios.
IEEE Robotics Autom. Lett., 2021

Dense Optical Flow from Event Cameras.
CoRR, 2021

TimeLens: Event-based Video Frame Interpolation.
CoRR, 2021

Time Lens: Event-Based Video Frame Interpolation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

How To Calibrate Your Event Camera.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

E-RAFT: Dense Optical Flow from Event Cameras.
Proceedings of the International Conference on 3D Vision, 2021

2020
Correction to: EKLT: Asynchronous Photometric Feature Tracking Using Events and Frames.
Int. J. Comput. Vis., 2020

EKLT: Asynchronous Photometric Feature Tracking Using Events and Frames.
Int. J. Comput. Vis., 2020

Fast Image Reconstruction with an Event Camera.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Event-Based Asynchronous Sparse Convolutional Networks.
Proceedings of the Computer Vision - ECCV 2020, 2020

Video to Events: Recycling Video Datasets for Event Cameras.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Learning Monocular Dense Depth from Events.
Proceedings of the 8th International Conference on 3D Vision, 2020

2019
Video to Events: Bringing Modern Computer Vision Closer to Event Cameras.
CoRR, 2019

End-to-End Learning of Representations for Asynchronous Event-Based Data.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018
Asynchronous, Photometric Feature Tracking Using Events and Frames.
Proceedings of the Computer Vision - ECCV 2018, 2018

ESIM: an Open Event Camera Simulator.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018


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