VSS-Net: Visual Semantic Self-Mining Network for Video Summarization

• Published in: IEEE transactions on circuits and systems for video technology Vol. 34; no. 4; pp. 2775 - 2788
• Main Authors: Zhang, Yunzuo, Liu, Yameng, Kang, Weili, Tao, Ran
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cognitive tasks; Computational modeling; Context; Context modeling; Feature extraction; Graphical representations; information exchange; Learning; Predictions; Segments; self-mining; semantic representation; Semantics; Streaming media; Target detection; Task analysis; temporal cues; Video data; Video summarization; Visualization

Video summarization, with the target to detect valuable segments given untrimmed videos, is a meaningful yet understudied topic. Previous methods primarily consider inter-frame and inter-shot temporal dependencies, which might be insufficient to pinpoint important content due to limited valuable inf...