Abstract
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.
Abstract (translated)
随着互联网带宽和存储空间的巨大增长，视频数据已经产生，发布并且爆发式地传播，成为当今大数据不可或缺的一部分。在本文中，我们重点回顾两个研究课题，旨在激发对视频的深入理解：视频分类和视频字幕。虽然视频分类专注于基于视频片段的语义内容（如人为操作或复杂事件）自动标注视频片段，但视频字幕会尝试生成完整且自然的句子，丰富视频分类中的单个标签，以捕捉视频中最具信息量的动态。此外，我们还提供了对评估这个充满活力的领域的技术进步至关重要的常用基准和比赛的评论。
URL
https://arxiv.org/abs/1609.06782
