Visual interestingness prediction: A benchmark framework and literature review
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 …
framework for image and video visual interestingness prediction. We propose a robust data …
Computational understanding of visual interestingness beyond semantics: literature survey and analysis of covariates
Understanding visual interestingness is a challenging task addressed by researchers in
various disciplines ranging from humanities and psychology to, more recently, computer …
various disciplines ranging from humanities and psychology to, more recently, computer …
Overview of the ImageCLEF 2022: Multimedia retrieval in medical, social media and nature applications
This paper presents an overview of the ImageCLEF 2022 lab that was organized as part of
the Conference and Labs of the Evaluation Forum–CLEF Labs 2022. ImageCLEF is an …
the Conference and Labs of the Evaluation Forum–CLEF Labs 2022. ImageCLEF is an …
Annotating, understanding, and predicting long-term video memorability
Memorability can be regarded as a useful metric of video importance to help make a choice
between competing videos. Research on computational understanding of video …
between competing videos. Research on computational understanding of video …
Deep learning for predicting image memorability
H Squalli-Houssaini, NQK Duong… - … on acoustics, speech …, 2018 - ieeexplore.ieee.org
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 …
important research subject in computer vision. This paper presents our computation model …
MMTF-14K: a multifaceted movie trailer feature dataset for recommendation and retrieval
In this paper we propose a new dataset, ie, the MMTF-14K multi-faceted dataset. It is
primarily designed for the evaluation of video-based recommender systems, but it also …
primarily designed for the evaluation of video-based recommender systems, but it also …
Unsupervised online learning for robotic interestingness with visual memory
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 …
exploration, or to decide which data to share for cooperation. These scenarios often require …
Deep multimodal features for movie genre and interestingness prediction
O Ben-Ahmed, B Huet - 2018 international conference on …, 2018 - ieeexplore.ieee.org
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 …
prediction based on the genre and affective impact of movie content. We hypothesize that …
[PDF][PDF] Overview of ImageCLEFfusion 2022 Task-Ensembling Methods for Media Interestingness Prediction and Result Diversification.
LD Stefan, MG Constantin… - CLEF (Working …, 2022 - gconstantin.aimultimedialab.ro
The 2022 ImageCLEFfusion task is the first edition of this task, targeting the creation of late
fusion or ensembling methods in two different scenarios:(i) the prediction of media visual …
fusion or ensembling methods in two different scenarios:(i) the prediction of media visual …
Stories of love and violence: zero-shot interesting events' classification for unsupervised tv series summarization
In this paper, we propose an unsupervised approach to generate TV series summaries
using screenplays that are composed of dialogue and scenic textual descriptions. In the last …
using screenplays that are composed of dialogue and scenic textual descriptions. In the last …