Multigranular Event Recognition of Personal Photo Albums
People are taking more photos than ever before in recent years. To effectively organize these personal photos, the photos are usually assigned to albums according to their events. An efficient way to manage our photos would be if we could recognize the events of the albums automatically. In this paper, we study the problem of recognizing events in personal photo albums. Recognizing events in photo albums is a new challenge since the contents of photos in albums are more complicated than in traditional single-photo tasks, since not all photos in an album are relevant to the event and a single photo in an album often fails to convey the meaningful event semantic behind the album. To solve this problem, we introduce an attention network to learn the representations of photo albums. Then, we adopt a hierarchical model to recognize events from coarse to fine using multigranular features. We evaluate our model on two real-world datasets consisting of personal albums; we find that our model achieves promising results.