Diverse Neural Photo Album Summarization
9th International Conference on Image Processing Theory, Tools and Applications (IPTA), İstanbul, Türkiye, 6 - 09 Kasım 2019, (Tam Metin Bildiri)
- Yayın Türü: Bildiri / Tam Metin Bildiri
- Cilt numarası:
- Doi Numarası: 10.1109/ipta.2019.8936084
- Basıldığı Şehir: İstanbul
- Basıldığı Ülke: Türkiye
- Hacettepe Üniversitesi Adresli: Evet
Özet
In this paper, we address the problem of learning to summarize personal photo albums. That is, given a photo album, we aim to select a small set of representative images from the album so that the extracted summary captures most of the story that is being told through the images. More specifically, we extend a recently proposed recurrent neural network based framework by employing a more effective way to represent images and, more importantly, adding a diversity term to the main objective. Our diversity term is based on the idea of jointly training a discriminator network to evaluate the diversity of the selected images. This alleviates the issue of selecting near-duplicate or semantically similar images, which is the primary shortcoming of the base approach. The experimental results show that our improved model produces better or comparable summaries, providing a good balance between quality and diversity.