Daniel Gehrig

@DanielGehrig6

#ComputerVision and #Robotics PostDoc @GRASPlab and @Penn.
Interested in the intersection of #DeepLearning, #ComputerVision and #Robotics.

Philadelphia, USA Joined October 2018

139 Following 290 Followers 26 Posts

Latest posts 5

Daniel Gehrig @DanielGehrig6 Jun 19, 2024

Happy to attend #CVPR2024 this year and meet new and old friends. Want to learn more about minimal solvers for event camera-based motion estimation? Check out poster 183 Thu at 17:15 - 18:45 in Arch 4A-E, and Oral #2 in Orals 4C Thu 13:00 - 14:30!

Davide Scaramuzza Verified account @davsca1 Jun 17, 2024

Meet us at #CVPR2024 this week! We will present several papers on #Nerf deblurring, #StateSpaceModels, and Motion Estimation on Manifolds for #eventcameras at the main conference and workshops! Full list with times, rooms, and links to PDFs, Code, and Videos: docs.google.com/document/d/1eq… @marcocannici @DanielGehrig6 @NikolaZubic5

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Daniel Gehrig @DanielGehrig6 Sep 13, 2023

Thanks @davsca1 and to all team members and collaborators who supported me during my PhD journey. Special thanks also to my reviewers who asked tough and thoughtful questions. I learned alot and made many friends along the way. Looking forward to what the future brings!

Davide Scaramuzza Verified account @davsca1 Sep 12, 2023

Congratulations to my student @DanielGehrig6 for successfully defending his Ph.D. in “Efficient, Data-Driven Perception with Event Cameras”! Many thanks to the external reviewers Marc Pollefeys @mapo1, Kostas Daniilidis @KostasPenn, and Andreas Geiger! Daniel has contributed deep-learning methods that combine #eventcamera data with standard images to achieve efficient, low-latency perception. His applications span feature tracking, object detection, and video frame interpolation. In particular, he proposed techniques for adapting deep geometric learning methods based on convolutional and graph neural networks to perform efficient and asynchronous event-by-event computation without sacrificing accuracy, reaching unprecedented low latency in object detection tasks! Congratulations, Daniel; it has been an honor to work with you!

- Video Recording of the PhD defense: youtu.be/ncNFqI44BnA
- Daniel's webpage (publications, source code, slides): danielgehrig18.github.io
- Google Scholar: scholar.google.com/citations?user…
@uzh_en @ERC_Research @nccrrobotics

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Daniel Gehrig @DanielGehrig6 Jun 25, 2021

Check out our paper "TimeLens: Event-based Video Frame Interpolation" at #CVPR2021 in Paper Session 12 at 12:00-14:30 CEST. I will be happy to answer any questions about our work!
@StepanTulyakov @MathiasGehrig @davsca1

Davide Scaramuzza Verified account @davsca1 Jun 14, 2021

We release our newest work on event cameras: "Time Lens". We use events to upsample low-framerate RGB HD video by over 50 times with only 1/40th of the memory footprint! #CVPR2021 Paper, code, datasets: rpg.ifi.uzh.ch/timelens
@DanielGehrig6 @MathiasGehrig

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Daniel Gehrig @DanielGehrig6 Jun 15, 2021

Very excited to share this work! It really shows that we can do amazing things with event cameras.

Davide Scaramuzza Verified account @davsca1 Jun 14, 2021

We release our newest work on event cameras: "Time Lens". We use events to upsample low-framerate RGB HD video by over 50 times with only 1/40th of the memory footprint! #CVPR2021 Paper, code, datasets: rpg.ifi.uzh.ch/timelens
@DanielGehrig6 @MathiasGehrig

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Daniel Gehrig @DanielGehrig6 Aug 24, 2020

Check out our poster at #ECCV2020 to learn more about "Event-based Asynchronous Sparse Convolutional Networks" using #eventcameras between 6:00-8:00 and 14:00-16:00 GMT. Joint work with @Messikommer1, @antoniloq and @davsca1.
Paper: rpg.ifi.uzh.ch/docs/ECCV20_Me…