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

We consider the task of identifying human actions visible in online videos.We focus on the widely spread genre of lifestyle vlogs, which consist of videosof people performing actions while verbally describing them. Our goal is toidentify if actions mentioned in the speech description of a video are visuallypresent. We construct a dataset with crowdsourced manual annotations of visibleactions, and introduce a multimodal algorithm that leverages informationderived from visual and linguistic clues to automatically infer which actionsare visible in a video. We demonstrate that our multimodal algorithmoutperforms algorithms based only on one modality at a time.

Identifying Visible Actions in Lifestyle Vlogs