论文标题
对Livebot的响应：基于视觉和文本上下文生成实时视频评论
Response to LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts
论文作者
论文摘要
实时视频评论系统是在线视频网站的新兴功能。最近，中国视频共享平台比利比利（Bilibili）推广了一个新颖的字幕系统，在该系统中，用户评论显示为“移动字幕”流在视频播放屏幕上，并实时向所有观众广播。 Livebot最近被引入为新颖的自动实时视频评论（ALVC）应用程序。这使现有视频流和现有观众评论的自动生成实时视频评论可以自动生成。在寻求重现原始Livebot论文中报告的基线结果时，我们发现使用项目代码库的重现结果与论文中报告的数字之间的差异。对这种情况的进一步检查表明，这可能是由于项目法规中的许多小问题引起的，包括培训和测试集之间的非显而易见的重叠。在本文中，我们详细研究了这些差异，并提出了替代基线实施，作为该领域其他研究人员的参考。
Live video commenting systems are an emerging feature of online video sites. Recently the Chinese video sharing platform Bilibili, has popularised a novel captioning system where user comments are displayed as streams of moving subtitles overlaid on the video playback screen and broadcast to all viewers in real-time. LiveBot was recently introduced as a novel Automatic Live Video Commenting (ALVC) application. This enables the automatic generation of live video comments from both the existing video stream and existing viewers comments. In seeking to reproduce the baseline results reported in the original Livebot paper, we found differences between the reproduced results using the project codebase and the numbers reported in the paper. Further examination of this situation suggests that this may be caused by a number of small issues in the project code, including a non-obvious overlap between the training and test sets. In this paper, we study these discrepancies in detail and propose an alternative baseline implementation as a reference for other researchers in this field.
