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

This report introduces our novel method named STHG for the Audio-VisualDiarization task of the Ego4D Challenge 2023. Our key innovation is that wemodel all the speakers in a video using a single, unified heterogeneous graphlearning framework. Unlike previous approaches that require a separatecomponent solely for the camera wearer, STHG can jointly detect the speechactivities of all people including the camera wearer. Our final method obtains61.1% DER on the test set of Ego4D, which significantly outperforms all thebaselines as well as last year's winner. Our submission achieved 1st place inthe Ego4D Challenge 2023. We additionally demonstrate that applying theoff-the-shelf speech recognition system to the diarized speech segments by STHGproduces a competitive performance on the Speech Transcription task of thischallenge.

STHG: Spatial-Temporal Heterogeneous Graph Learning for Advanced Audio-Visual Diarization