The Interestingness Dataset is a collection of movie excerpts and key-frames and their corresponding ground-truth files based on the classification into interesting and non-interesting samples. It is intended to be used for assessing the quality of methods for predicting the interestingness of multimedia content.

The data has been produced by the MediaEval 2016 Predicting Interestingness Task organizers and was used in the context of this benchmark. A detailed description of the benchmark can be found on our Data Description page. The license conditions are mentioned on the Download page.



We would like to thank the MediaEval benchmark and their organizers for their support in the creation of this dataset. We also would like to thank the different co-organizers and advisories for the task:

and of course our annotators.



If you make use of the Interestingness Dataset, or refer to its results, please use the following citation:

C.-H. Demarty, M. Sjöberg, B. Ionescu, T.-T. Do, H. Wang, N. Q. Duong, and F. Lefebvre. Mediaeval 2016 predicting media interestingness task. In Proc. Of the MediaEval 2016 Workshop, Hilversum, Netherlands, Oct. 20-21, 2016 (pdf).


Title = {MediaEval 2016 Predicting Media Interestingness Task},

Author = {Claire-H\'{e}l\`{e}ne Demarty and Mats Sj\¨{o}berg and Bogdan Ionescu and Than-Toan Do and Hanli Wang and Ngoc Q.K. Duong and Fr\'{e}d\'{e}rique Lefebvre},

Booktitle = {Proc. of the MediaEval 2016 Workshop, Hilversum, Netherlands, Oct. 20-21},

Year = {2016},


We use cookies on our website to support technical features that enhance your user experience.

We also use analytics & advertising services. To opt-out click for more information.