arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1910.11102cs.CVcs.MM

Vatex Video Captioning Challenge 2020: Multi-View Features and Hybrid Reward Strategies for Video Captioning

Institute of Automation, Chinese Academy of Sciences(中国科学院自动化研究所);University of Science and Technology Beijing(北京科技大学);Wuhan University(武汉大学)

Xinxin Zhu, Longteng Guo, Peng Yao, Shichen Lu, Wei Liu, Jing Liu

英文摘要:

This report describes our solution for the VATEX Captioning Challenge 2020, which requires generating descriptions for the videos in both English and Chinese languages. We identified three crucial factors that improve the performance, namely: multi-view features, hybrid reward, and diverse ensemble. Based on our method of VATEX 2019 challenge, we achieved significant improvements this year with more advanced model architectures, combination of appearance and motion features, and careful hyper-parameters tuning. Our method achieves very competitive results on both of the Chinese and English video captioning tracks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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