Our method uses machine learning techniques together with a large-scale training dataset of manually created GIFs. The dataset consists of about 100k GIFs that people created from videos. Using this data we train a Deep Neural Network algorithm that learns to understand what makes GIFs awesome. Finally, we use this model to automatically rank video segments and generate GIFs from the best and most interesting ones.

Thanks to a new deep learning system from Yahoo! Research, GIFs are just one more art form--in addition to poetry and calligraphy, to name a few--that computers are quickly mastering. A computer made that all on its own. In fact, not only did a computer make the above GIF, it actually scanned the original video and decided which bits had the highest GIF potential; a video went in, and a slew of appealing GIFs came out. We're on our way to what you could call a fully automated, bean-to-bar, GIF-making solution. Research in New York do, you could call it Video2GIF.