Mining Multi-Modality Spatio-Temporal Cues for Video Important Person Identification

ArXi:2605.28604v1 Announce Type: cross Identifying key individuals in video scenes is essential for applications such as automated video editing and intelligent surveillance. Current methods primarily focus on static images and immediate visual cues, overlooking the rich spatio-temporal information in videos. This leads to the phenomenon of Temporal Importance Shift (TIS), wherein individuals deemed significant in early frames may be ted as the entire temporal context is considered. To address this, we.