Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction
The work by Michelle Rüegg that contributed to the paper “Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction”, presented at RA-L 2021 lead to the NCCR Swiss Robotics Master Award!
May 30, 2021
Learning Monocular Dense Depth from Events
Nov 25, 2020
Event-based Asynchronous Sparse Convolutional Networks
This work received a Best Presentation Award at the ONSVP workshop at ICRA 2021 in Xi’an.
Aug 23, 2020
Video to Events: Recycling Video Dataset for Event Cameras
Jun 16, 2020
Fast Image Reconstruction with an Event Camera
Mar 1, 2020
End-to-End Learning of Representations for Asynchronous Event-Based Data
Oct 27, 2019
EKLT: Asynchronous, Photometric Feature Tracking using Events and Frames
This paper received an oral at ECCV 2018 and was invited as a journal extension at IJCV!
Aug 22, 2019
Asynchronous, Photometric Feature Tracking using Events and Frames
This paper lead to an oral at ECCV 2018 and was invited to a journal extension by IJCV.
Sep 8, 2018