Event cameras are bio-inspired sensors that capture the per-pixel intensity changes
asynchronously and produce event streams encoding the time, pixel position, and polarity …

Vision-based localization systems, namely visual odometry (VO) and visual inertial odometry
(VIO), have attracted great attention recently. They are regarded as critical modules for …

Traditional frame-based cameras inevitably suffer from motion blur due to long exposure
times. As a kind of bio-inspired camera, the event camera records the intensity changes in …

In this paper, we propose an end-to-end learning framework for event-based motion
deblurring in a self-supervised manner, where real-world events are exploited to alleviate …

Dynamic Vision Sensor (DVS) event camera output includes uninformative background
activity (BA) noise events that increase dramatically under dim lighting. Existing denoising …

Event cameras are an exciting, new sensor modality enabling high-speed imaging with
extremely low-latency and wide dynamic range. Unfortunately, most machine learning …

Event cameras sense per-pixel intensity changes and produce asynchronous event streams
with high dynamic range and less motion blur, showing advantages over the conventional …

Modern image-based deblurring methods usually show degenerate performance in low-light
conditions since the images often contain most of the poorly visible dark regions and a few …

Neuromorphic vision sensor is a new bio-inspired imaging paradigm that emerged in recent
years, which continuously sensing luminance intensity and firing asynchronous spikes …

Abstract We present Ev-NeRF, a Neural Radiance Field derived from event data. While
event cameras can measure subtle brightness changes in high frame rates, the …