Will People Like Your Image?

The wide distribution of digital devices as well as cheap storage allow us to take series of photos making sure not to miss any specific beautiful moment. Thereby, the huge and constantly growing image assembly makes it quite timeconsuming to manually pick the best shots afterwards. Even more challenging, finding the most aesthetically pleasing images that might also be worth sharing is a largely subjective task in which general rules rarely apply. Nowadays, online platforms allow users to “like” or favor certain content with a single click. As we aim to predict the aesthetic quality of images, we now make use of such multi-user agreements. More precisely, we assemble a large data set of 380K images with associated meta information and derive a score to rate how visually pleasing a given photo is. Further, to predict the aesthetic quality of any arbitrary image or video, we transfer the obtained model into a deep learning problem. Our proposed model of aesthetics is validated in a user study. We demonstrate our results on applications for resorting photo collections, capturing the best shot on mobile devices and aesthetic key-frame extraction from videos.