5 citations · 20 across the 13 of their papers we have counts for
9 papers · 1 filter
Capsules as viewpoint learners for human pose estimation
Nicola Garau, Nicola Conci
The task of human pose estimation (HPE) deals with the ill-posed problem of estimating the 3D position of human joints directly from images and videos. In recent literature, most o…
Interpretable part-whole hierarchies and conceptual-semantic relationships in neural networks
Nicola Garau, Niccolò Bisagno, Zeno Sambugaro +1
Deep neural networks achieve outstanding results in a large variety of tasks, often outperforming human experts. However, a known limitation of current neural architectures is the…
DECA: Deep viewpoint-Equivariant human pose estimation using Capsule Autoencoders
Nicola Garau, Niccolò Bisagno, Piotr Bródka +1
Human Pose Estimation (HPE) aims at retrieving the 3D position of human joints from images or videos. We show that current 3D HPE methods suffer a lack of viewpoint equivariance, n…
Flood Detection via Twitter Streams using Textual and Visual Features
Firoj Alam, Zohaib Hassan, Kashif Ahmad +4
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 T…
Visual Sentiment Analysis from Disaster Images in Social Media
Syed Zohaib Hassan, Kashif Ahmad, Steven Hicks +4
The increasing popularity of social networks and users' tendency towards sharing their feelings, expressions, and opinions in text, visual, and audio content, have opened new oppor…
Deriving Emotions and Sentiments from Visual Content: A Disaster Analysis Use Case
Kashif Ahmad, Syed Zohaib, Nicola Conci +1
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…
Sentiment Analysis from Images of Natural Disasters
Syed Zohaib, Kashif Ahmad, Nicola Conci +1
Social media have been widely exploited to detect and gather relevant information about opinions and events. However, the relevance of the information is very subjective and rather…
Multi-Modal Machine Learning for Flood Detection in News, Social Media and Satellite Sequences
Kashif Ahmad, Konstantin Pogorelov, Mohib Ullah +4
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 Soci…
Active Learning for Event Detection in Support of Disaster Analysis Applications
Naina Said, Kashif Ahmad, Nicola Conci +1
Disaster analysis in social media content is one of the interesting research domains having abundance of data. However, there is a lack of labeled data that can be used to train ma…