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Found 5 papers, 3 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
Event Cameras, Contrast Maximization and Reward Functions: An Analysis
The versatility of this approach has lead to a flurry of research in recent years, but no in-depth study of the reward chosen during optimization has yet been made.
CED: Color Event Camera Dataset
Event cameras are novel, bio-inspired visual sensors, whose pixels output asynchronous and independent timestamped spikes at local intensity changes, called 'events'.
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).
