D&M: Enriching E-commerce Videos with Sound Effects by Key Moment Detection and SFX Matching
Jingyu Liu, Minquan Wang, Ye Ma, Bo Wang, Aozhu Chen, Quan Chen, Peng Jiang, Xirong Li
Abstract
Videos showcasing specific products are increasingly important for E-commerce. Key moments naturally exist as the first appearance of a specific product, presentation of its distinctive features, the presence of a buying link, etc. Adding proper sound effects (SFX) to such moments, or video decoration with SFX (VDSFX), is crucial for enhancing user engaging experience. Previous work adds SFX to videos by video-to-SFX matching at a holistic level, lacking the ability of adding SFX to a specific moment. Meanwhile, previous studies on video highlight detection or video moment retrieval consider only moment localization, leaving moment to SFX matching untouched. By contrast, we propose in this paper D&M, a unified method that accomplishes key moment detection and moment-to-SFX matching simultaneously. Moreover, for the new VDSFX task we build a large-scale dataset SFX-Moment from an E-commerce video creation platform. For a fair comparison, we build competitive baselines by extending a number of current video moment detection methods to the new task. Extensive experiments on SFX-Moment show the superior performance of the proposed method over the baselines.
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- Joint Visual and Audio Learning for Video Highlight DetectionTaivanbat Badamdorj, Mrigank Rochan, Yang Wang, Li ChengICCV 2021 · 91 citations
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