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

A self-supervised adaptive low-light video enhancement method, called SALVE,is proposed in this work. SALVE first enhances a few key frames of an inputlow-light video using a retinex-based low-light image enhancement technique.For each keyframe, it learns a mapping from low-light image patches to enhancedones via ridge regression. These mappings are then used to enhance theremaining frames in the low-light video. The combination of traditionalretinex-based image enhancement and learning-based ridge regression leads to arobust, adaptive and computationally inexpensive solution to enhance low-lightvideos. Our extensive experiments along with a user study show that 87% ofparticipants prefer SALVE over prior work.

SALVE: Self-supervised Adaptive Low-light Video Enhancement