DCA:Diversified Co-attention Towards Informative Live Video Commenting
We focus on the task of Automatic Live Video Commenting(ALVC),which aims to generate real-time video comments with both video frames and other viewers'comments as inputs.A major challenge in this task is how to properly leverage the rich and diverse information carried by video and text.In this paper,we aim to collect diversified information from video and text for informative comment generation.To achieve this,we propose a Diversified Co-Attention(DCA)model for this task.Our model builds bidirectional interactions between video frames and surrounding comments from multiple perspectives via metric learning,to collect a diversified and informative context for comment generation.We also propose an effective parameter orthogonalization technique to avoid excessive overlap of information learned from differ-ent perspectives.Results show that our approach outperforms existing methods in the ALVC task,achieving new state-of-the-art results.
Zhihan Zhang Zhiyi Yin Shuhuai Ren Xinhang Li Shicheng Li
School of Electronic Engineering and Computer Science,Peking University,Beijing,China School of Software Engineering,Huazhong University of Science and Technology,Wuhan,China College of Software,Beijing University of Aeronautics and Astronautics,Beijing,China
国际会议
9th CCF International Conference on Natural Language Processing and Chinese Computing (NLPCC 2020)
郑州
英文
854-866
2020-10-14（万方平台首次上网日期，不代表论文的发表时间）