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- Technische Universität BerlinDE49 papers
- Keio UniversityJP4 papers
- University of ZurichCH4 papers
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)DE3 papers
- Einstein Center for Neurosciences BerlinDE3 papers
- ETH ZurichCH3 papers
- Excellence Cluster UniverseDE3 papers
- Hong Kong University of Science and TechnologyHK3 papers
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- Karlsruhe Institute of TechnologyDE3 papers
- University of PennsylvaniaUS3 papers
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5 papers · 2 filters
A Fast Geometric Regularizer to Mitigate Event Collapse in the Contrast Maximization Framework
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Event cameras are emerging vision sensors and their advantages are suitable for various applications such as autonomous robots. Contrast maximization (CMax), which provides state-o…
Secrets of Event-Based Optical Flow
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Event cameras respond to scene dynamics and offer advantages to estimate motion. Following recent image-based deep-learning achievements, optical flow estimation methods for event…
Event Collapse in Contrast Maximization Frameworks
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Contrast maximization (CMax) is a framework that provides state-of-the-art results on several event-based computer vision tasks, such as ego-motion or optical flow estimation. Howe…
Multi-Event-Camera Depth Estimation and Outlier Rejection by Refocused Events Fusion
Suman Ghosh, Guillermo Gallego
Event cameras are bio-inspired sensors that offer advantages over traditional cameras. They operate asynchronously, sampling the scene at microsecond resolution and producing a str…
Event-aided Direct Sparse Odometry
Javier Hidalgo-Carrió, Guillermo Gallego, Davide Scaramuzza
We introduce EDS, a direct monocular visual odometry using events and frames. Our algorithm leverages the event generation model to track the camera motion in the blind time betwee…