In this paper, we report on the creation of a publicly available, common evaluation
framework for image and video visual interestingness prediction. We propose a robust data …

Understanding visual interestingness is a challenging task addressed by researchers in
various disciplines ranging from humanities and psychology to, more recently, computer …

Memorability of media content such as images and videos has recently become an
important research subject in computer vision. This paper presents our computation model …

Autonomous robots frequently need to detect “interesting” scenes to decide on further
exploration, or to decide which data to share for cooperation. These scenarios often require …

In this paper, we propose a multimodal framework for video segment interestingness
prediction based on the genre and affective impact of movie content. We hypothesize that …

In this paper, we explore the problem of interesting scene prediction for mobile robots. This
area is currently underexplored but is crucial for many practical applications such as …

The selection of the best photos in personal albums is a task that is often faced by
photographers. This task can become laborious when the photo collection is large and it …

The recent advancement in Multimedia Analytical, Computer Vision (CV), and Artificial
Intelligence (AI) algorithms resulted in several interesting tools allowing an automatic …

In the context of the ever growing quantity of multimedia content from social, news and
educational platforms, generating meaningful recommendations and ratings now requires a …

With the explosive increase in the consumption of multimedia content in recent years, the
field of media interestingness analysis has gained a lot of attention. This paper tackles the …