15 citations · 28 across the 15 of their papers we have counts for
16 papers
Human-Inspired Social Engagement Analysis via Interpretable Mutual Visual Attention
Urwa Fatima, Mohammad Zohaib, Francesca Odone +1
Understanding social interactions from non-verbal visual data is important for behavior analysis and activity monitoring. We propose an interpretable computational model of social…
3D Classification of Paramagnetic Rim Lesions in Multiple Sclerosis via Asymmetric QSM-FLAIR Modeling
Veronica Pignedoli, Giacomo Boffa, Nicoletta Noceti +3
Paramagnetic rim lesions (Rim) identified on susceptibility-sensitive MRI have recently emerged as a specific biomarker of chronic active inflammation in Multiple Sclerosis (MS…
Disentangled representations of microscopy images
Jacopo Dapueto, Vito Paolo Pastore, Nicoletta Noceti +1
Microscopy image analysis is fundamental for different applications, from diagnosis to synthetic engineering and environmental monitoring. Modern acquisition systems have granted t…
Transferring disentangled representations: bridging the gap between synthetic and real images
Jacopo Dapueto, Nicoletta Noceti, Francesca Odone
Developing meaningful and efficient representations that separate the fundamental structure of the data generation mechanism is crucial in representation learning. However, Disenta…
Anticipation through Head Pose Estimation: a preliminary study
Federico Figari Tomenotti, Nicoletta Noceti
The ability to anticipate others' goals and intentions is at the basis of human-human social interaction. Such ability, largely based on non-verbal communication, is also a key to…
Shortcuts for causal discovery of nonlinear models by score matching
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco +1
The use of simulated data in the field of causal discovery is ubiquitous due to the scarcity of annotated real data. Recently, Reisach et al., 2021 highlighted the emergence of pat…
Assumption violations in causal discovery and the robustness of score matching
Francesco Montagna, Atalanti A. Mastakouri, Elias Eulig +5
When domain knowledge is limited and experimentation is restricted by ethical, financial, or time constraints, practitioners turn to observational causal discovery methods to recov…
Scalable Causal Discovery with Score Matching
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco +2
This paper demonstrates how to discover the whole causal graph from the second derivative of the log-likelihood in observational non-linear additive Gaussian noise models. Leveragi…
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise
Francesco Montagna, Nicoletta Noceti, Lorenzo Rosasco +2
Causal discovery methods are intrinsically constrained by the set of assumptions needed to ensure structure identifiability. Moreover additional restrictions are often imposed in o…
Robots with Different Embodiments Can Express and Influence Carefulness in Object Manipulation
Linda Lastrico, Luca Garello, Francesco Rea +4
Humans have an extraordinary ability to communicate and read the properties of objects by simply watching them being carried by someone else. This level of communicative skills and…
Synthesis and Execution of Communicative Robotic Movements with Generative Adversarial Networks
Luca Garello, Linda Lastrico, Alessandra Sciutti +3
Object manipulation is a natural activity we perform every day. How humans handle objects can communicate not only the willfulness of the acting, or key aspects of the context wher…
HHP-Net: A light Heteroscedastic neural network for Head Pose estimation with uncertainty
Giorgio Cantarini, Federico Figari Tomenotti, Nicoletta Noceti +1
In this paper we introduce a novel method to estimate the head pose of people in single images starting from a small set of head keypoints. To this purpose, we propose a regression…
Property-Aware Robot Object Manipulation: a Generative Approach
Luca Garello, Linda Lastrico, Francesco Rea +3
When transporting an object, we unconsciously adapt our movement to its properties, for instance by slowing down when the item is fragile. The most relevant features of an object a…
Action similarity judgment based on kinematic primitives
Vipul Nair, Paul Hemeren, Alessia Vignolo +7
Understanding which features humans rely on -- in visually recognizing action similarity is a crucial step towards a clearer picture of human action perception from a learning and…
The role of ego vision in view-invariant action recognition
Gaurvi Goyal, Nicoletta Noceti, Francesca Odone +1
Analysis and interpretation of egocentric video data is becoming more and more important with the increasing availability and use of wearable cameras. Exploring and fully understan…
Scale Invariant Interest Points with Shearlets
Miguel A. Duval-Poo, Nicoletta Noceti, Francesca Odone +1
Shearlets are a relatively new directional multi-scale framework for signal analysis, which have been shown effective to enhance signal discontinuities such as edges and corners at…