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

Egocentric videos capture sequences of human activities from a first-personperspective and can provide rich multimodal signals. However, most currentlocalization methods use third-person videos and only incorporate visualinformation. In this work, we take a deep look into the effectiveness ofaudiovisual context in detecting actions in egocentric videos and introduce asimple-yet-effective approach via Observing, Watching, and Listening (OWL). OWLleverages audiovisual information and context for egocentric temporal actionlocalization (TAL). We validate our approach in two large-scale datasets,EPIC-Kitchens, and HOMAGE. Extensive experiments demonstrate the relevance ofthe audiovisual temporal context. Namely, we boost the localization performance(mAP) over visual-only models by +2.23% and +3.35% in the above datasets.

OWL (Observe, Watch, Listen): Audiovisual Temporal Context for Localizing Actions in Egocentric Videos