UBiSS: A Unified Framework for Bimodal Semantic Summarization of Videos

• URL: http://arxiv.org/abs/2406.16301v1
• Date: Mon, 24 Jun 2024 03:55:25 GMT
• Title: UBiSS: A Unified Framework for Bimodal Semantic Summarization of Videos
• Authors: Yuting Mei, Linli Yao, Qin Jin,
• Abstract summary: We focus on a more comprehensive video summarization task named Bimodal Semantic Summarization of Videos (BiSSV) We propose a Unified framework UBiSS for the BiSSV task, which models the saliency information in the video and generates a TM-summary and VM-summary simultaneously. Experiments show that our unified framework achieves better performance than multi-stage summarization pipelines.
• Score: 52.161513027831646
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: With the surge in the amount of video data, video summarization techniques, including visual-modal(VM) and textual-modal(TM) summarization, are attracting more and more attention. However, unimodal summarization inevitably loses the rich semantics of the video. In this paper, we focus on a more comprehensive video summarization task named Bimodal Semantic Summarization of Videos (BiSSV). Specifically, we first construct a large-scale dataset, BIDS, in (video, VM-Summary, TM-Summary) triplet format. Unlike traditional processing methods, our construction procedure contains a VM-Summary extraction algorithm aiming to preserve the most salient content within long videos. Based on BIDS, we propose a Unified framework UBiSS for the BiSSV task, which models the saliency information in the video and generates a TM-summary and VM-summary simultaneously. We further optimize our model with a list-wise ranking-based objective to improve its capacity to capture highlights. Lastly, we propose a metric, $NDCG_{MS}$, to provide a joint evaluation of the bimodal summary. Experiments show that our unified framework achieves better performance than multi-stage summarization pipelines. Code and data are available at https://github.com/MeiYutingg/UBiSS.

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