In the era of smartphones and social media, where everyone is able to capture the moment and share it online […]
Better, Faster and Lighter Video Retrieval
In this post, we explain the basics behind our paper “DnS: Distill-and-Select for Efficient and Accurate Video Indexing and Retrieval”, […]
Online Disinformation in Europe
Last year, we had the opportunity to conduct a desk research study in an effort to map the landscape of […]
Geolocating images in the globe with high accuracy
In this post we explain the basics behind our paper “Leveraging EfficientNet and Contrastive Learning for Accurate Global-scale Location Estimation” […]
Operation-wise Attention Network for Tampering Localization Fusion
In this post, we explain the basics behind our paper “Operation-wise Attention Network for Tampering Localization Fusion”, which has been accepted for publication at this year’s Content-Based Multimedia Indexing conference (CBMI 2021).
MeVer @ MediaEval2020
The MediaEval Multimedia Evaluation benchmark was founded in 2008 as VideoCLEF and in 2011 became an independent benchmarking initiative. Each year it offers tasks that are related to multimedia retrieval, analysis, and exploration.
Deepfakes: An Emerging Internet Threat and their Detection
Towards the end of 2020, I had the opportunity to give a talk on Deepfakes in the 60th AI4EU WebCafe. […]
MeVer tools for Image and Video Verification within WeVerify
WeVerify is an EU granted project that aims to address the complex content verification challenges through a participatory verification approach, open-source algorithms, low-overhead human-in-the-loop machine learning and intuitive visualizations. The MeVer team leads the ‘Cross-modal Disinformation Detection and Content Verification’ work package and in collaboration with the University of Sheffield (USFD) have developed tools that will bring together features from text, images and videos to tackle the challenge of cross-modal disinformation detection and content verification.
Video similarity based on audio
In this post, we explain the basics behind our paper “Audio-based Near-Duplicate Video Retrieval with Audio Similarity Learning,” which has […]
MeVer participation in Deepfake detection challenge
It has been almost 2 months since the final deadline for the challenge on the Kaggle platform. Competition organizers have just finalized the standings (13th of June 2020) in the private leaderboard. A Kaggle staff member mentioned in a discussion that competition organizers took their time to validate winning submissions and ensure that they comply with the competition rules. This process resulted in the disqualification of the top-performing team due to the usage of external data without proper license. This caused a lot of disturbance among the Kaggle community mainly because the competition rules were vague.