Publications

Ling Gao*, Daniel Gehrig*, Hang Su, Davide Scaramuzza, Laurent Kneip (2024). An N-Point Linear Solver for Line and Motion Estimation with Event Cameras. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Asude Aydin, Mathias Gehrig, Daniel Gehrig, Davide Scaramuzza (2024). A Hybrid ANN-SNN Architecture for Low-Power and Low-Latency Visual Perception. IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Daniel Gehrig, Davide Scaramuzza (2024). Low Latency Automotive Vision with Event Cameras. Nature.

Roberto Pellerito, Marco Cannici, Daniel Gehrig, Joris Belhadj, Olivier Dubois-Matra, Massimo Casasco, Davide Scaramuzza (2024). End-to-End Learned Event- and Image-based Visual Odometry. arXiv.

Nikola Zubic*, Daniel Gehrig*, Mathias Gehrig, Davide Scaramuzza (2023). From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detection. Int. Conf. Comput. Vis. (ICCV).

Ling Gao, Su Hao, Daniel Gehrig, Marco Cannici, Davide Scaramuzza, Laurent Kneip (2023). A 5-Point Minimal Solver for Event Camera Relative Motion Estimation. Int. Conf. Comput. Vis. (ICCV).

Benedek Forrai*, Takahiro Miki*, Daniel Gehrig*, Marco Hutter, Davide Scaramuzza (2023). Event-based Agile Object Catching with a Quadrupedal Robot. IEEE Int. Conf. Robot. Autom. (ICRA).

Daniel Gehrig, Davide Scaramuzza (2022). Pushing the Limits of Asynchronous Graph-based Object Detection with Event Cameras. IEEE Robot. Autom. Lett. (RA-L).

Florian Mahlknecht, Daniel Gehrig, Jeremy Nash, Friedrich M. Rockenbauer, Benjamin Morrell, Jeff Delaune, Davide Scaramuzza (2022). Exploring Event Camera-based Odometry for Planetary Robots. IEEE Robot. Autom. Lett. (RA-L).

Stepan Tulyakov, Alfredo Bochicchio, Daniel Gehrig, Stamatios Georgoulis, Yuanyou Li, Davide Scaramuzza (2022). Time Lens++: Event-based Frame Interpolation with Parametric Non-linear Flow and Multi-scale Fusion. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).