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).
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.
How similar are two videos?
In this post we explain the basics behind our paper with title “ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning” which was accepted for an oral presentation at this year’s International Conference on Computer Vision (ICCV 2019).