Accelerated by the tremendous increase in Internet bandwidth and storage space, video data has been generated, published and spread explosively, becoming an indispensable part of today's big data. In this paper, we focus on reviewing two lines of research aiming to stimulate the comprehension of videos with deep learning: video classification and video captioning. While video classification concentrates on automatically labeling video clips based on their semantic contents like human actions or complex events, video captioning attempts to generate a complete and natural sentence, enriching the single label as in video classification, to capture the most informative dynamics in videos. In addition, we also provide a review of popular benchmarks and competitions, which are critical for evaluating the technical progress of this vibrant field.
翻译:由于互联网带宽和存储空间的大幅增加,视频数据被迅速生成、出版和传播,成为当今大数据不可或缺的组成部分。在本文中,我们侧重于审查两条研究线,目的是通过深层学习促进理解视频:视频分类和视频字幕。视频分类侧重于基于其语义内容的自动标签视频剪辑,如人类行动或复杂事件,视频字幕试图生成完整和自然的句子,丰富视频分类中的单一标签,以捕捉视频中信息最丰富的动态。此外,我们还提供了对流行基准和竞赛的审查,这对评价这个充满活力的领域的技术进步至关重要。