4 papers
TEn-CATG:Text-Enriched Audio-Visual Video Parsing with Multi-Scale Category-Aware Temporal Graph
Yaru Chen, Faegheh Sardari, Peiliang Zhang +4
Audio-visual video parsing (AVVP) aims to detect event categories and their temporal boundaries in videos, typically under weak supervision. Existing methods mainly focus on (i) im…
Teacher-Guided Pseudo Supervision and Cross-Modal Alignment for Audio-Visual Video Parsing
Yaru Chen, Ruohao Guo, Liting Gao +4
Weakly-supervised audio-visual video parsing (AVVP) seeks to detect audible, visible, and audio-visual events without temporal annotations. Previous work has emphasized refining gl…
TeMTG: Text-Enhanced Multi-Hop Temporal Graph Modeling for Audio-Visual Video Parsing
Yaru Chen, Peiliang Zhang, Fei Li +4
Audio-Visual Video Parsing (AVVP) task aims to parse the event categories and occurrence times from audio and visual modalities in a given video. Existing methods usually focus on…
Audio-Visual Instance Segmentation
Ruohao Guo, Xianghua Ying, Yaru Chen +11
In this paper, we propose a new multi-modal task, termed audio-visual instance segmentation (AVIS), which aims to simultaneously identify, segment and track individual sounding obj…