Paper Title
Detect-to-Summarize Network for Video Summarization: A Versatile Approach
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: Authors
Keywords
modeling, video summarization, and anchor-free detection.
Abstract
This suggested study presents the Detect-to-Summonize network (DSNet), a supervised video summarizing architecture. Using the first method required a lot of work to create a video overview. The anchor free and anchor-based technique with temporal consideration for video summarization is used. The anchor-based approach is used with temporal interest with location regression and importance prediction. Interestingly, information about the quality and accuracy of the summary produced is presented in both the positive and negative sections. We anticipate segment placements and video frame significance ratings in advance, which somewhat mitigates the anchor-free method's temporal suggestion shortcomings. More precisely, the interest detection system can be easily integrated with commercially available supervised video summarizing techniques. We use the Tsum and SumMe datasets to give an examination of anchor-based versus anchor-free techniques. It is evident from the trial's outcomes that both anchor-based and anchor-free strategies are effective.
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How To Cite (APA)
Ms.Kaveri kadam, Ms.Sarita sapkal, Dr.Geetha Chllarge, Ms.Vandana Rupnar, & Dr.Swati Shekapure (August-2024). Detect-to-Summarize Network for Video Summarization: A Versatile Approach. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(8), b38-b44. https://ijnrd.org/papers/IJNRD2408097.pdf
Issue
Volume 9 Issue 8, August-2024
Pages : b38-b44
Other Publication Details
Paper Reg. ID: IJNRD_226375
Published Paper Id: IJNRD2408097
Downloads: 000122253
Research Area: Engineering
Author Type: Indian Author
Country: karad, Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2408097.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2408097
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