Open-Ended Multi-Modal Relational Reasoning for Video Question Answering

• URL: http://arxiv.org/abs/2012.00822v4
• Date: Tue, 11 Jun 2024 06:12:52 GMT
• Title: Open-Ended Multi-Modal Relational Reasoning for Video Question Answering
• Authors: Haozheng Luo, Ruiyang Qin, Chenwei Xu, Guo Ye, Zening Luo,
• Abstract summary: The primary focus of this agent is to assist individuals using language-based interactions within video-based scenes. Our proposed method integrates video recognition technology and natural language processing models within the robotic agent.
• Score: 1.8699569122464073
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we introduce a robotic agent specifically designed to analyze external environments and address participants' questions. The primary focus of this agent is to assist individuals using language-based interactions within video-based scenes. Our proposed method integrates video recognition technology and natural language processing models within the robotic agent. We investigate the crucial factors affecting human-robot interactions by examining pertinent issues arising between participants and robot agents. Methodologically, our experimental findings reveal a positive relationship between trust and interaction efficiency. Furthermore, our model demonstrates a 2\% to 3\% performance enhancement in comparison to other benchmark methods.

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