Title Generation for User Generated Videos

Human-authored clickbait has competition: here’s an algorithm that can automatically generate titles for videos. Combine it with a neural net that learns which titles get the most traffic and pretty soon the Internet will be able to curate cat videos without human intervention.

The researchers (Kuo-Hao Zeng, Tseng-Hung Chen, Juan Carlos Niebles, and Min Sun) recognized that most video captioning algorithms were trained on isolated clips rather than the longer, rambling versions that people are more likely to upload. So their approach identifies the most salient event in the video and captions that.

They also used an interesting additional data source: sentences that don’t have a paired video. This let them learn from a much larger vocabulary. 

Of course, as the recent debacle of Facebook’s trending algorithm demonstrates, purely AI-run automation is frequently inferior to a human augmented with AI support. Centaurs tend to outperform both humans and computers. Where better AI helps is that it lets you feed more automation into the AI half of the collaboration, empowering the human even more.

Speaking as someone who has produced a lot of stock video clips, this tech would really come in handy. Captioning and keywording videos takes a lot of thought, and searching through thousands of badly-keyworded videos is draining. A better way to automate 80% of the task is incredibly useful.

http://arxiv.org/abs/1608.07068