Event-specific Image Importance

Yufei Wang, Zhe Lin, Xiaohui Shen, Radomír Měch, Gavin Miller, Garrison W. Cottrell

When creating a photo album of an event, people typically select a few important images to keep or share. Modeling this selection process will assist automatic photo selection and album summarization. In this project, we show that the selection of important images is consistent among different viewers, and that this selection process is related to the event type of the album. We introduce the concept of event-specific image importance. We propose a Convolutional Neural Network (CNN) based method to predict the image importance score of a given event album, using a novel rank loss function and a progressive training scheme. Results demonstrate that our method significantly outperforms various baseline methods.

paper Code

CUFED Dataset

The CUration of Flickr Events Dataset (CUFED) dataset is an event curation dataset containing 1883 albums. Each album describes an event, and the event type of albums are from 23 most common events in our daily life, ranging from Wedding to Nature Trip. The size of albums varies between 30 and 100 images.

For each album, images in the album are rated by 5 participants by their importance/interestingness score based on the content and event type of the album. The score is the "event-specific image importance" of the image.

Download CUFED

Citing CUFED

If you use CUFED for your research, please cite:

  title={Event-specific Image Importance},
  author={Wang, Yufei and Lin, Zhe and Shen, Xiaohui and Mech, Radomir and Miller, Gavin and Cottrell, Garrison. W.},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},