Search Results for author:
Found 5 papers, 3 papers with code
Deep Event Visual Odometry
To remove the dependency on additional sensors and to push the limits of using only a single event camera, we present Deep Event VO (DEVO), the first monocular event-only system with strong performance on a large number of real-world benchmarks.
Masked Event Modeling: Self-Supervised Pretraining for Event Cameras
The models pretrained with MEM are also label-efficient and generalize well to the dense task of semantic image segmentation.
E-NeRF: Neural Radiance Fields from a Moving Event Camera
We also show that combining events and frames can overcome failure cases of NeRF estimation in scenarios where only a few input views are available without requiring additional regularization.
TUM-VIE: The TUM Stereo Visual-Inertial Event Dataset
The event cameras contain a large sensor of 1280x720 pixels, which is significantly larger than the sensors used in existing stereo event datasets (at least by a factor of ten).
Event-Based Feature Tracking in Continuous Time with Sliding Window Optimization
We propose a novel method for continuous-time feature tracking in event cameras.
