Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
37th (2023)
Session ID : 1O5-GS-7-02
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Saliency Map Estimation with ViNet for Ad Movie with active scene and satatic area
*Kazuhiro ONISHITaro WATANABE
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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

A saliency map prediction system using ViNet is proposed to improve the accuracy reduction dependent on the speed of moving objects in saliency map prediction considering the characteristics of spatiotemporally interwoven video and still image domains. By solving the problem of partial accuracy reduction in advertising videos with intense motion, and by outputting saliency maps that are closer to the human gaze, the system improves the accuracy of video advertising production and further enhances brand lift and recognition effects. Stable output is confirmed in qualitative evaluation using test-produced video advertisements, and improved accuracy is obtained in quantitative evaluation using multiple indicators. This study will further accelerate a new production flow for advertising videos that takes into account the viewer's perspective in advance.

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© 2023 The Japanese Society for Artificial Intelligence
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