Visual Place Recognition with Probabilistic Vertex Voting. - Mathias Gehrig; Elena Stumm; Timo Hinzmann; Roland Siegwart (CoRR, 2016)

Visual place recognition with probabilistic voting. - Mathias Gehrig; Elena Stumm; Timo Hinzmann; Roland Siegwart (ICRA, 2017)

Focus Is All You Need: Loss Functions for Event-Based Vision. - Guillermo Gallego 002; Mathias Gehrig; Davide Scaramuzza 001 (CVPR, 2019)

Beauty and the Beast: Optimal Methods Meet Learning for Drone Racing. - Elia Kaufmann; Mathias Gehrig; Philipp Foehn; René Ranftl; Alexey Dosovitskiy; Vladlen Koltun; Davide Scaramuzza 001 (ICRA, 2019)

Video to Events: Bringing Modern Computer Vision Closer to Event Cameras. - Daniel Gehrig; Mathias Gehrig; Javier Hidalgo-Carrió; Davide Scaramuzza 001 (CoRR, 2019)

Video to Events: Recycling Video Datasets for Event Cameras. - Daniel Gehrig; Mathias Gehrig; Javier Hidalgo-Carrió; Davide Scaramuzza 001 (CVPR, 2020)

Towards Low-Latency High-Bandwidth Control of Quadrotors using Event Cameras. - Rika Sugimoto Dimitrova; Mathias Gehrig; Dario Brescianini; Davide Scaramuzza 001 (ICRA, 2020)

Event-Based Angular Velocity Regression with Spiking Networks. - Mathias Gehrig; Sumit Bam Shrestha; Daniel Mouritzen; Davide Scaramuzza 001 (ICRA, 2020)

E-RAFT: Dense Optical Flow from Event Cameras. - Mathias Gehrig; Mario Millhäusler; Daniel Gehrig; Davide Scaramuzza 001 (3DV, 2021)

How To Calibrate Your Event Camera. - Manasi Muglikar; Mathias Gehrig; Daniel Gehrig; Davide Scaramuzza 001 (CVPR Workshops, 2021)

Time Lens: Event-Based Video Frame Interpolation. - Stepan Tulyakov; Daniel Gehrig; Stamatios Georgoulis; Julius Erbach; Mathias Gehrig; Yuanyou Li; Davide Scaramuzza 001 (CVPR, 2021)

TimeLens: Event-based Video Frame Interpolation. - Stepan Tulyakov; Daniel Gehrig; Stamatios Georgoulis; Julius Erbach; Mathias Gehrig; Yuanyou Li; Davide Scaramuzza 001 (CoRR, 2021)

Dense Optical Flow from Event Cameras. - Mathias Gehrig; Mario Millhäusler; Daniel Gehrig; Davide Scaramuzza 001 (CoRR, 2021)

DSEC: A Stereo Event Camera Dataset for Driving Scenarios. - Mathias Gehrig; Willem Aarents; Daniel Gehrig; Davide Scaramuzza 001 (IEEE Robotics Autom. Lett., 2021)

Combining Events and Frames Using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction. - Daniel Gehrig; Michelle Rüegg; Mathias Gehrig; Javier Hidalgo-Carrió; Davide Scaramuzza 001 (IEEE Robotics Autom. Lett., 2021)

AlphaPilot: autonomous drone racing. - Philipp Foehn; Dario Brescianini; Elia Kaufmann; Titus Cieslewski; Mathias Gehrig; Manasi Muglikar; Davide Scaramuzza 001 (Auton. Robots, 2022)

Dense Continuous-Time Optical Flow from Events and Frames. - Mathias Gehrig; Manasi Muglikar; Davide Scaramuzza 001 (CoRR, 2022)

Bridging the Gap Between Events and Frames Through Unsupervised Domain Adaptation. - Nico Messikommer; Daniel Gehrig; Mathias Gehrig; Davide Scaramuzza 001 (IEEE Robotics Autom. Lett., 2022)

Recurrent Vision Transformers for Object Detection with Event Cameras. - Mathias Gehrig; Davide Scaramuzza 001 (CVPR, 2023)

Data-Driven Feature Tracking for Event Cameras. - Nico Messikommer; Carter Fang; Mathias Gehrig; Davide Scaramuzza 001 (CVPR, 2023)

Neuromorphic Optical Flow and Real-time Implementation with Event Cameras. - Yannick Schnider; Stanislaw Wozniak; Mathias Gehrig; Jules Lecomte; Axel von Arnim; Luca Benini; Davide Scaramuzza 001; Angeliki Pantazi (CVPR Workshops, 2023)

From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detection. - Nikola Zubic; Daniel Gehrig; Mathias Gehrig; Davide Scaramuzza 001 (ICCV, 2023)

From Chaos Comes Order: Ordering Event Representations for Object Detection. - Nikola Zubic; Daniel Gehrig; Mathias Gehrig; Davide Scaramuzza 001 (CoRR, 2023)

A Hybrid ANN-SNN Architecture for Low-Power and Low-Latency Visual Perception. - Asude Aydin; Mathias Gehrig; Daniel Gehrig; Davide Scaramuzza 001 (CVPR Workshops, 2024)

LEOD: Label-Efficient Object Detection for Event Cameras. - Ziyi Wu; Mathias Gehrig; Qing Lyu 008; Xudong Liu; Igor Gilitschenski (CVPR, 2024)

State Space Models for Event Cameras. - Nikola Zubic; Mathias Gehrig; Davide Scaramuzza 001 (CVPR, 2024)

Reinforcement Learning Meets Visual Odometry. - Nico Messikommer; Giovanni Cioffi; Mathias Gehrig; Davide Scaramuzza 001 (ECCV (59), 2024)

Revisiting Token Pruning for Object Detection and Instance Segmentation. - Yifei Liu; Mathias Gehrig; Nico Messikommer; Marco Cannici; Davide Scaramuzza 001 (WACV, 2024)

Dense Continuous-Time Optical Flow From Event Cameras. - Mathias Gehrig; Manasi Muglikar; Davide Scaramuzza 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

A Unified Framework for Event-Based Frame Interpolation With Ad-Hoc Deblurring in the Wild. - Lei Sun 009; Daniel Gehrig; Christos Sakaridis; Mathias Gehrig; Jingyun Liang; Peng Sun; Zhijie Xu; Kaiwei Wang; Luc Van Gool; Davide Scaramuzza 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Data-Driven Feature Tracking for Event Cameras With and Without Frames. - Nico Messikommer; Carter Fang; Mathias Gehrig; Giovanni Cioffi; Davide Scaramuzza 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)