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.

Polychronis from the MeVer team had the opportunity to visit DeepTrace Labs, a company based in Amsterdam, focusing on deepfake detection. MeVer and DeepTrace have recently started collaborating on the problem of DeepFake detection, which MeVer faces in the context of the WeVerify project. As part of this collaboration, the two teams also joined forces to tackle the Kaggle’s DeepFake Detection Challenge. The goal of the challenge is to build effective solutions that can help detect DeepFakes and manipulated media. The final deadline for submissions is March 31, 2020.

A lot of our research and development activities rely on large collections of web media content sourced from social media platforms, such as YouTube and Twitter, and then manually curated and annotated by our researchers with the purpose of creating “ground truth” datasets. This helps us train machine learning models on specific tasks and then benchmark those models along with competing approaches in order to select the best method per case. It goes without saying that we spend loads of effort on developing scripts for crawling, monitoring, extracting and fetching the necessary data and content related to the target task, and then even more effort on curating, cleaning and labeling (aka annotating) the collected datasets. Especially, content labelling is particularly challenging due to the subjective nature of the task, e.g. different people may perceive the same content as belonging to different categories, while there are additional issues in specific annotation tasks, e.g. when dealing with NSFW and disturbing content.

On the 24th of April 2020, a huge coronavirus-related hackathon started, the EUvsVirus Hackathon, organized by the European Commission. Over 20,900 people across the EU and beyond took part, with 2,150 solutions submitted in areas including health and life (898), business continuity (381), remote working and education (270), social and political cohesion (452), digital finance (75) and other challenges (83).

The Context Aggregation and Analysis tool was developed by the MeVer team within the InVID project and continues to evolve within the WeVerify project. The tool aims to facilitate the verification of user-generated videos posted by three well-known platforms – YouTube, Facebook and Twitter. It collects information surrounding the video, analyses and filters it and creates a verification report that is then presented to the end user (journalist) who is responsible to inspect the verification cues and decide about the video veracity.

The International Conference on Computer Vision (ICCV) is one of the major computer vision conferences, hosted by IEEE and CVF. Along with the Computer Vision and Pattern Recognition Conference (CVPR) and the European Conference on Computer Vision (ECCV), they are the three top tier conferences in the world in the field of computer vision.

The Truth and Trust Online conference achieved its mission to bring together people with different backgrounds, levels of seniority, origin and also from various disciplines. It covered a wide range of issues around the challenge of misinformation and the 257 participants had two days of amazing talks from people of well known companies, universities, media organizations, NGOs, such as Facebook, Google, Twitter, Microsoft, BBC, Full Fact and others.

The Thessaloniki edition of the Researchers’ Night was held on September 27 and tried to bring researchers closer to society and inspire more young people to get involved with research. Researchers’ Night 2019 took place at Thessaloniki Concert Hall. Photo by Symeon Papadopoulos A large crowd of people of all ages attended the event and more than 100 of them were interested in the hot topic of misinformation. The Media Verification team of CERTH-ITI was there to demonstrate tools for media verification developed within the InVID and WeVerify projects.

MeVer has contributed to the editing and authoring of the brand new book “Video Verification in the Fake News Era” published by Springer last week. The book covers a range of recent technological advances and practical tools for discovering, verifying and visualizing social media video content, and managing related rights. In today’s increasingly disinformation-fraught media landscape, access to sophisticated editing and content management tools and the ease with which fake information spreads in electronic networks, require the entire news and media industries to carefully verify third-party content before publishing it.

In this post we explain the basics behind our paper with title “ViSiL: Fine-grained Spatio-Temporal Video Similarity Learning” [1] which was accepted for an oral presentation at this year’s International Conference on Computer Vision (ICCV 2019). Let’s consider two arbitrary videos, such as the ones displayed below. Also, we consider that the right video serves as query and the left as a candidate match. For the better understanding of the method, we select two near-duplicate videos.