EgoAdapt: Enhancing Robustness in Egocentric Interactive Speaker Detection Under Missing Modalities
TTM (Talking to Me) task is a pivotal component in understanding human social interactions, aiming to determine who is engaged in conversation with the camera-wearer. Traditional models often face challenges in real-world scenarios due to missing visual data, neglecting the role of head orientation, and background noise. This study addresses these limitations by introducing EgoAdapt, an adaptive framework designed for robust egocentric "Talking to Me" speaker detection under missing modalities. Specifically, EgoAdapt incorporates three key modules: (1) a Visual Speaker Target Recognition (VSTR) module that captures head orientation as a non-verbal cue and lip movement as a verbal cue, all...
| Authors | Xinyuan Qian, Xinjia Zhu, Alessio Brutti et al. |
|---|---|
| Primary category | cs.MM |
| Published | 18 March 2026 |
| Last updated at source | 18 March 2026 |
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