Daniel Gehrig
Daniel Gehrig
Ph.D. candidate, University of Zurich
Verified email at ifi.uzh.ch
Title
Cited by
Cited by
Year
ESIM: an open event camera simulator
H Rebecq, D Gehrig, D Scaramuzza
Conference on Robot Learning, 969-982, 2018
562018
Asynchronous, Photometric Feature Tracking using Events and Frames
D Gehrig
Robotics and Perception Group, University of Zurich, 2018
452018
Asynchronous, photometric feature tracking using events and frames
D Gehrig, H Rebecq, G Gallego, D Scaramuzza
Proceedings of the European Conference on Computer Vision (ECCV), 750-765, 2018
452018
End-to-end learning of representations for asynchronous event-based data
D Gehrig, A Loquercio, KG Derpanis, D Scaramuzza
Proceedings of the IEEE International Conference on Computer Vision, 5633-5643, 2019
362019
EKLT: Asynchronous photometric feature tracking using events and frames
D Gehrig, H Rebecq, G Gallego, D Scaramuzza
International Journal of Computer Vision 128 (3), 601-618, 2020
142020
Fast image reconstruction with an event camera
C Scheerlinck, H Rebecq, D Gehrig, N Barnes, R Mahony, D Scaramuzza
The IEEE Winter Conference on Applications of Computer Vision, 156-163, 2020
142020
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
7*2020
Event-based Asynchronous Sparse Convolutional Networks
N Messikommer, D Gehrig, A Loquercio, D Scaramuzza
Proceedings of the European Conference on Computer Vision (ECCV), 2020
12020
Learning Monocular Dense Depth from Events
J Hidalgo-Carrió, D Gehrig, D Scaramuzza
arXiv preprint arXiv:2010.08350, 2020
2020
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Articles 1–9