This paper introduces a groundbreaking low-complexity lossless compression method for encoding asynchronous event sequences, designed for efficient memory usage and low-power hardware integration.
This paper tackles the speed-resolution trade-off using event cameras. Event cameras are efficient highspeed vision sensors that asynchronously measure changes in brightness intensity with microsecond resolution.
This paper tackles the speed-resolution trade-off using event cameras. Event cameras are efficient highspeed vision sensors that asynchronously measure changes in brightness intensity with microsecond resolution.
This paper showcases the viability of integrating conventional algorithms with event-based data, transformed into a frame format while preserving the unique benefits of event cameras.
This paper proposes a novel, computationally efficient regularizer to mitigate event collapse in the CMax framework. From a theoretical point of view, the regularizer is designed based on geometric principles of motion field deformation (measuring area rate of change along point trajectories).