Recent works have shown that it is possible to automatically predict intrinsic image properties like memorability. In this paper, we take a step forward addressing the question: "Can we make an image more memorable?". Methods for automatically increasing image memorability would have an impact in many application fields like education, gaming or advertising. Our work is inspired by the popular editing-by-applying-filters paradigm adopted in photo editing applications, like Instagram and Prisma. In this context, the problem of increasing image memorability maps to that of retrieving "memorabilizing" filters or style "seeds". Still, users generally have to go through most of the available filters before finding the desired solution, thus turning the editing process into a resource and time consuming task. In this work, we show that it is possible to automatically retrieve the best style seeds for a given image, thus remarkably reducing the number of human attempts needed to find a good m...
How to make an image more memorable? A deep style transfer approach / Siarohin, Aliaksandr; Zen, Gloria; Alameda-Pineda, Xavier; Ricci, Elisa; Sebe, Nicu; Majtanovic, Cveta. - (2017), pp. 322-329. (Intervento presentato al convegno 17th ACM International Conference on Multimedia Retrieval, ICMR 2017 tenutosi a Bucharest nel 2017) [10.1145/3078971.3078986].
How to make an image more memorable? A deep style transfer approach
Siarohin, Aliaksandr;Zen, Gloria;Alameda-Pineda, Xavier;Ricci, Elisa;Sebe, Nicu;Majtanovic, Cveta
2017-01-01
Abstract
Recent works have shown that it is possible to automatically predict intrinsic image properties like memorability. In this paper, we take a step forward addressing the question: "Can we make an image more memorable?". Methods for automatically increasing image memorability would have an impact in many application fields like education, gaming or advertising. Our work is inspired by the popular editing-by-applying-filters paradigm adopted in photo editing applications, like Instagram and Prisma. In this context, the problem of increasing image memorability maps to that of retrieving "memorabilizing" filters or style "seeds". Still, users generally have to go through most of the available filters before finding the desired solution, thus turning the editing process into a resource and time consuming task. In this work, we show that it is possible to automatically retrieve the best style seeds for a given image, thus remarkably reducing the number of human attempts needed to find a good m...| File | Dimensione | Formato | |
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