2 code implementations • 4 Apr 2023 • Jheng-Hong Yang, Carlos Lassance, Rafael Sampaio de Rezende, Krishna Srinivasan, Miriam Redi, Stéphane Clinchant, Jimmy Lin
This paper presents the AToMiC (Authoring Tools for Multimedia Content) dataset, designed to advance research in image/text cross-modal retrieval.
1 code implementation • 10 May 2021 • KayYen Wong, Miriam Redi, Diego Saez-Trumper
Templates are tags used by expert Wikipedia editors to indicate content issues, such as the presence of "non-neutral point of view" or "contradictory articles", and serve as a strong signal for detecting reliability issues in a revision.
no code implementations • 18 Jun 2020 • Edgar Meij, Tara Safavi, Chenyan Xiong, Gianluca Demartini, Miriam Redi, Fatma Özcan
The KG-BIAS 2020 workshop touches on biases and how they surface in knowledge graphs (KGs), biases in the source data that is used to create KGs, methods for measuring or remediating bias in KGs, but also identifying other biases such as how and which languages are represented in automatically constructed KGs or how personal KGs might incur inherent biases.
1 code implementation • 23 Jan 2020 • Tiziano Piccardi, Miriam Redi, Giovanni Colavizza, Robert West
Wikipedia, the free online encyclopedia that anyone can edit, is one of the most visited sites on the Web and a common source of information for many users.
Computers and Society
1 code implementation • 28 Feb 2019 • Miriam Redi, Besnik Fetahu, Jonathan Morgan, Dario Taraborelli
In this paper, we aim to provide an empirical characterization of the reasons why and how Wikipedia cites external sources to comply with its own verifiability guidelines.
no code implementations • 1 Nov 2017 • Luca M. Aiello, Rossano Schifanella, Miriam Redi, Stacey Svetlichnaya, Frank Liu, Simon Osindero
Exposure to beauty is double-edged: following people who produce high-quality content increases one's probability of uploading better photos; however, an excessive imbalance between the quality generated by a user and the user's neighbors leads to a decline in engagement.
2 code implementations • 6 Sep 2016 • Yale Song, Miriam Redi, Jordi Vallmitjana, Alejandro Jaimes
Our system selects attractive thumbnails by analyzing various visual quality and aesthetic metrics of video frames, and performs a clustering analysis to determine the relevance to video content, thus making the resulting thumbnails more representative of the video.
Multimedia
no code implementations • 7 Jun 2016 • Nikolaos Pappas, Miriam Redi, Mercan Topkara, Brendan Jou, Hongyi Liu, Tao Chen, Shih-Fu Chang
The impact of culture in visual emotion perception has recently captured the attention of multimedia research.
no code implementations • 16 Aug 2015 • Brendan Jou, Tao Chen, Nikolaos Pappas, Miriam Redi, Mercan Topkara, Shih-Fu Chang
Our work expressly focuses on the uniqueness of culture and language in relation to human affect, specifically sentiment and emotion semantics, and how they manifest in social multimedia.
no code implementations • 28 May 2015 • Miriam Redi, Daniele Quercia, Lindsay T. Graham, Samuel D. Gosling
To choose restaurants and coffee shops, people are increasingly relying on social-networking sites.
no code implementations • 13 May 2015 • Rossano Schifanella, Miriam Redi, Luca Aiello
We propose to use a computer vision method to surface beautiful pictures from the immense pool of near-zero-popularity items, and we test it on a large dataset of creative-commons photos on Flickr.
no code implementations • 28 Jan 2015 • Miriam Redi, Nikhil Rasiwasia, Gaurav Aggarwal, Alejandro Jaimes
Digital portrait photographs are everywhere, and while the number of face pictures keeps growing, not much work has been done to on automatic portrait beauty assessment.
no code implementations • CVPR 2014 • Miriam Redi, Neil O Hare, Rossano Schifanella, Michele Trevisiol, Alejandro Jaimes
The notion of creativity, as opposed to related concepts such as beauty or interestingness, has not been studied from the perspective of automatic analysis of multimedia content.