Daniel Gehrig
  • Bio
  • Papers
  • Talks
  • News
  • Experience
  • Projects
  • Teaching
  • Publications
    • A Hybrid ANN-SNN Architecture for Low-Power and Low-Latency Visual Perception
    • An N-Point Linear Solver for Line and Motion Estimation with Event Cameras
    • Low Latency Automotive Vision with Event Cameras
    • End-to-End Learned Event- and Image-based Visual Odometry
    • A 5-Point Minimal Solver for Event Camera Relative Motion Estimation
    • From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detection
    • Event-based Agile Object Catching with a Quadrupedal Robot
    • Pushing the Limits of Asynchronous Graph-based Object Detection with Event Cameras
    • Exploring Event Camera-based Odometry for Planetary Robots
    • AEGNN: Asynchronous Event-based Graph Neural Networks
    • ESS: Learning Event-based Semantic Segmentation from Still Images
    • Multi-Bracket High Dynamic Range Imaging with Event Cameras
    • Time Lens++: Event-based Frame Interpolation with Parametric Non-linear Flow and Multi-scale Fusion
    • Are High-Resolution Event Cameras Really Needed?
    • Bridging the Gap between Events and Frames through Unsupervised Domain Adaptation
    • E-RAFT: Dense Optical Flow from Event Cameras
    • How to Calibrate Your Event Camera
    • Time Lens: Event-based Video Frame Interpolation
    • Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction
    • DSEC: A Stereo Event Camera Dataset for Driving Scenarios
    • Learning Monocular Dense Depth from Events
    • Event-based Asynchronous Sparse Convolutional Networks
    • Video to Events: Recycling Video Dataset for Event Cameras
    • Fast Image Reconstruction with an Event Camera
    • End-to-End Learning of Representations for Asynchronous Event-Based Data
    • EKLT: Asynchronous, Photometric Feature Tracking using Events and Frames
    • ESIM: an Open Event Camera Simulator
    • Asynchronous, Photometric Feature Tracking using Events and Frames
  • Projects
  • Blog
    • 🎉 I started as a postdoctoral researcher at the GRASP Lab at UPenn.
    • 🧠 I successfully defended my Ph.D. with Summa Cum Laude!
  • Recent & Upcoming Talks
    • Efficient Data-driven Perception with Event Cameras
    • Efficient Data-driven Perception with Event Cameras
    • Efficient Event Processing with Geometric Deep Learning
  • Experience
  • Teaching
    • Lecturer for "Vision Algorithms for Mobile Robotics"

🧠 I successfully defended my Ph.D. with Summa Cum Laude!

Sep 7, 2023 · 1 min read

I’d like to thanks everyone who has helped and supported me on this journey. A special thanks goes out to my supervisor Prof. Davide Scaramuzza, and my reviewers, Prof. Kostas Daniilidis, Prof. Andreas Geiger and Prof. Marc Pollefeys!

Last updated on Sep 7, 2023
Ph.D.
Daniel Gehrig
Authors
Daniel Gehrig
Postdoctoral Researcher
← 🎉 I started as a postdoctoral researcher at the GRASP Lab at UPenn. May 13, 2024

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