no code implementations • 5 Dec 2023 • Niccolò Bisagno, Nicola Garau, Antonio Luigi Stefani, Nicola Conci
Simulation is a powerful tool to easily generate annotated data, and a highly desirable feature, especially in those domains where learning models need large training datasets.
no code implementations • 13 Feb 2023 • Nicola Garau, Nicola Conci
We further test our network on multiple datasets, both in the RGB and depth domain, from seen and unseen viewpoints and in the viewpoint transfer task.
1 code implementation • CVPR 2022 • Nicola Garau, Niccolò Bisagno, Zeno Sambugaro, Nicola Conci
When it comes to critical applications as autonomous driving, security and safety, medicine and health, the lack of interpretability of the network behavior tends to induce skepticism and limited trustworthiness, despite the accurate performance of such systems in the given task.
no code implementations • 22 Nov 2021 • Syed Zohaib Hassan, Kashif Ahmad, Michael A. Riegler, Steven Hicks, Nicola Conci, Paal Halvorsen, Ala Al-Fuqaha
The Visual Sentiment Analysis task is being offered for the first time at MediaEval.
1 code implementation • ICCV 2021 2021 • Nicola Garau, Giulia Martinelli, Piotr Bròdka, Niccolò Bisagno, Nicola Conci
Human pose estimation (HPE) from RGB and depth images has recently experienced a push for viewpoint-invariant and scale-invariant pose retrieval methods.
1 code implementation • ICCV 2021 • Nicola Garau, Niccolò Bisagno, Piotr Bródka, Nicola Conci
Human Pose Estimation (HPE) aims at retrieving the 3D position of human joints from images or videos.
Ranked #1 on Pose Estimation on ITOP top-view
2 code implementations • CVPR 2021 • Alireza Zaeemzadeh, Niccolo Bisagno, Zeno Sambugaro, Nicola Conci, Nazanin Rahnavard, Mubarak Shah
In this paper, we argue that OOD samples can be detected more easily if the training data is embedded into a low-dimensional space, such that the embedded training samples lie on a union of 1-dimensional subspaces.
no code implementations • 30 Nov 2020 • Firoj Alam, Zohaib Hassan, Kashif Ahmad, Asma Gul, Michael Reiglar, Nicola Conci, Ala Al-Fuqaha
The paper presents our proposed solutions for the MediaEval 2020 Flood-Related Multimedia Task, which aims to analyze and detect flooding events in multimedia content shared over Twitter.
no code implementations • 4 Sep 2020 • Syed Zohaib Hassan, Kashif Ahmad, Steven Hicks, Paal Halvorsen, Ala Al-Fuqaha, Nicola Conci, Michael Riegler
While sentiment analysis of text streams has been widely explored in literature, sentiment analysis from images and videos is relatively new.
no code implementations • 3 Feb 2020 • Kashif Ahmad, Syed Zohaib, Nicola Conci, Ala Al-Fuqaha
Sentiment analysis aims to extract and express a person's perception, opinions and emotions towards an entity, object, product and a service, enabling businesses to obtain feedback from the consumers.
no code implementations • 10 Oct 2019 • Syed Zohaib, Kashif Ahmad, Nicola Conci, Ala Al-Fuqaha
Social media have been widely exploited to detect and gather relevant information about opinions and events.
no code implementations • 7 Oct 2019 • Kashif Ahmad, Konstantin Pogorelov, Mohib Ullah, Michael Riegler, Nicola Conci, Johannes Langguth, Ala Al-Fuqaha
In this paper we present our methods for the MediaEval 2019 Mul-timedia Satellite Task, which is aiming to extract complementaryinformation associated with adverse events from Social Media andsatellites.
no code implementations • 27 Sep 2019 • Naina Said, Kashif Ahmad, Nicola Conci, Ala Al-Fuqaha
Disaster analysis in social media content is one of the interesting research domains having abundance of data.
no code implementations • CVPR 2015 • Davide Conigliaro, Paolo Rota, Francesco Setti, Chiara Bassetti, Nicola Conci, Nicu Sebe, Marco Cristani
In the dataset, a massive annotation has been carried out, focusing on the spectators at different levels of details: at a higher level, people have been labeled depending on the team they are supporting and the fact that they know the people close to them; going to the lower levels, standard pose information has been considered (regarding the head, the body) but also fine grained actions such as hands on hips, clapping hands etc.