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New method rethinks talk-to-me detection in egocentric videos

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced a new approach to detecting when someone in an egocentric video is speaking directly to the camera wearer. This method reframes the problem from a binary classification to an online, frame-level prediction, accounting for various non-talk-to-me (TTM) states like talking to others or self-talking. A new dataset, the Online TTM Dataset, was created with approximately 900,000 annotated frames to support this formulation. A multimodal model integrating audio, visual, and speech-semantic cues achieved a 75.5% frame-level F1 score on TTM detection. AI

IMPACT Improves understanding of social interactions in egocentric video, potentially enabling more sophisticated AI assistants.

RANK_REASON The cluster contains an academic paper detailing a new method and dataset for a computer vision task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New method rethinks talk-to-me detection in egocentric videos

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The cluster contains an academic paper detailing a new method and dataset for a computer vision task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Feiyu Du, Xi He, Jia Li, Yapeng Tian, Weili Wu ·

    Talking to Me or Someone Else? Rethinking Talk-to-Me Detection in Egocentric Videos

    arXiv:2609.14118v1 Announce Type: cross Abstract: Online understanding of who is talking to the camera wearer is a key capability for egocentric social interaction. However, existing talk-to-me (TTM) studies are commonly formulated as offline clip-level recognition, which is poor…

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