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 started as a postdoctoral researcher at the GRASP Lab at UPenn.

May 13, 2024·
Daniel Gehrig
Daniel Gehrig
· 1 min read

I joined the GRASP Lab to work on the intersection of computer vision, robotics and machine learning. I am looking forward to collaborations and what the future brings!

Last updated on May 13, 2024
Postdoc
Daniel Gehrig
Authors
Daniel Gehrig
Postdoctoral Researcher
🧠 I successfully defended my Ph.D. with Summa Cum Laude! Sep 7, 2023 →

© 2024 Me. This work is licensed under CC BY NC ND 4.0

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