English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Event cameras are emerging imaging technology that offers advantages overconventional frame-based imaging sensors in dynamic range and sensing speed.Complementing the rich texture and color perception of traditional imageframes, the hybrid camera system of event and frame-based cameras enableshigh-performance imaging. With the assistance of event cameras, high-qualityimage/video enhancement methods make it possible to break the limits oftraditional frame-based cameras, especially exposure time, resolution, dynamicrange, and frame rate limits. This paper focuses on five event-aided image andvideo enhancement tasks (i.e., event-based video reconstruction, event-aidedhigh frame rate video reconstruction, image deblurring, image super-resolution,and high dynamic range image reconstruction), provides an analysis of theeffects of different event properties, a real-captured and ground truth labeledbenchmark dataset, a unified benchmarking of state-of-the-art methods, and anevaluation for two mainstream event simulators. In detail, this paper collectsa real-captured evaluation dataset EventAid for five event-aided image/videoenhancement tasks, by using "Event-RGB" multi-camera hybrid system, taking intoaccount scene diversity and spatiotemporal synchronization. We further performquantitative and visual comparisons for state-of-the-art algorithms, provide acontrolled experiment to analyze the performance limit of event-aided imagedeblurring methods, and discuss open problems to inspire future research.

EventAid: Benchmarking Event-aided Image/Video Enhancement Algorithms with Real-captured Hybrid Dataset