These are the projects selected
Application Track projects 5
JECT-CLONE
JECT – Creative Landscapes of News
Application Track Project
Vision
The aim of the JECT-CLONE project is to deliver new computational creativity capabilities as a software-as-a-service (SaaS) that will autonomously generate novel themes, angles and voices for stories and send them regularly using existing channels to journalists and editors who are subscribed to the service.
VIREO
Visually appealing Image Recommendation based on Article Content using Artificial Intelligence
Application Track Project
Vision
VIREO is a digital interactive solution that uses AI techniques to recommend images to professionals in the News and Media industry, allowing them to create visually compelling articles and enhance the reading experience for media consumers.
NLMIE
Natural Language Media Indexing Engine
Application Track Project
Vision
NLMIE aims to fuse Natural Language Processing with Computer vision in order to modernise audio visual archives.
MBD
Mindbugs Discovery
Application Track Project
Vision
MindBugs project unites artists, journalists and programmers against misinformation.
magnet
Automatic Recommendation of In-Context Media Content to Support Exploratory Research in Journalism
Application Track Project
Vision
magnet is a tool to support journalists in the early phase of an article production by automatically resurfacing content from previous activities, relevant for the current moment.
Research Track projects 5
CAMOUFLAGE
Controllable AnonyMizatiOn throUgh diFfusion-based image coLlection GEneration
Research Track Project
Vision
Diffusion models for extreme image anonymization in social media.
ELMER
Efficient Long-term Multi-modal vidEo Retrieval
Research Track Project
Vision
To develop an efficient system for content retrieval that can handle multi-modal audio, image, text, and video data, especially for footage that is longer than 10 seconds.
HoloNeXT
Holographic transmission and Neural radiance fields for a novel Xr production Tool
Research Track Project
Vision
Novel XR Media Production Tool integrating two volumetric/XR technologies represented by 1) Neural Radiance Field scene modelling and 2) holographic real-time video volumetric transmission.
CLIP LENS
CLIP models, Looking for Enhanced New Systems (LENS)
Research Track Project
Vision
CLIP LENS aims to improve AI-based systems such as image classifiers and search engines through generative data augmentation and CLIP.
VolEvol
Generation of Meaningful Representations of Volume Data Through Evolutionary Learning
Research Track Project
Vision
The project aims to facilitate the rendering of images from volume data by using evolutionary algorithms to search for rendering parameters based on quality and diversity-oriented optimization objectives.