This paper investigates event-based shape from polarization using Spiking Neural Networks (SNNs), introducing the Single-Timestep and Multi-Timestep Spiking UNets for effective and efficient surface normal estimation.
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.