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Found 4 papers, 2 papers with code
Reducing the Sim-to-Real Gap for Event Cameras
We present strategies for improving training data for event based CNNs that result in 20-40% boost in performance of existing state-of-the-art (SOTA) video reconstruction networks retrained with our method, and up to 15% for optic flow networks.
Ranked #3 on
Video Reconstruction
on MVSEC
3D Sensing of a Moving Object with a Nodding 2D LIDAR and Reconfigurable Mirrors
Perception in 3D has become standard practice for a large part of robotics applications.
Event-Based Motion Segmentation by Motion Compensation
In contrast to traditional cameras, whose pixels have a common exposure time, event-based cameras are novel bio-inspired sensors whose pixels work independently and asynchronously output intensity changes (called "events"), with microsecond resolution.
Simultaneous Optical Flow and Segmentation (SOFAS) using Dynamic Vision Sensor
We present an algorithm (SOFAS) to estimate the optical flow of events generated by a dynamic vision sensor (DVS).
