1 citations · 2 across the 6 of their papers we have counts for
9 papers
TrackFlow: Multi-Object Tracking with Normalizing Flows
Gianluca Mancusi, Aniello Panariello, Angelo Porrello +3
The field of multi-object tracking has recently seen a renewed interest in the good old schema of tracking-by-detection, as its simplicity and strong priors spare it from the compl…
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?
Matteo Fabbri, Guillem Braso, Gianluca Maugeri +6
Deep learning-based methods for video pedestrian detection and tracking require large volumes of training data to achieve good performance. However, data acquisition in crowded pub…
Inter-Homines: Distance-Based Risk Estimation for Human Safety
Matteo Fabbri, Fabio Lanzi, Riccardo Gasparini +3
In this document, we report our proposal for modeling the risk of possible contagiousity in a given area monitored by RGB cameras where people freely move and interact. Our system,…
Compressed Volumetric Heatmaps for Multi-Person 3D Pose Estimation
Matteo Fabbri, Fabio Lanzi, Simone Calderara +2
In this paper we present a novel approach for bottom-up multi-person 3D human pose estimation from monocular RGB images. We propose to use high resolution volumetric heatmaps to mo…
Domain Translation with Conditional GANs: from Depth to RGB Face-to-Face
Matteo Fabbri, Guido Borghi, Fabio Lanzi +3
Can faces acquired by low-cost depth sensors be useful to catch some characteristic details of the face? Typically the answer is no. However, new deep architectures can generate RG…
Can Adversarial Networks Hallucinate Occluded People With a Plausible Aspect?
Federico Fulgeri, Matteo Fabbri, Stefano Alletto +2
When you see a person in a crowd, occluded by other persons, you miss visual information that can be used to recognize, re-identify or simply classify him or her. You can imagine i…
Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World
Matteo Fabbri, Fabio Lanzi, Simone Calderara +3
Multi-People Tracking in an open-world setting requires a special effort in precise detection. Moreover, temporal continuity in the detection phase gains more importance when scene…
Face-from-Depth for Head Pose Estimation on Depth Images
Guido Borghi, Matteo Fabbri, Roberto Vezzani +2
Depth cameras allow to set up reliable solutions for people monitoring and behavior understanding, especially when unstable or poor illumination conditions make unusable common RGB…
Generative Adversarial Models for People Attribute Recognition in Surveillance
Matteo Fabbri, Simone Calderara, Rita Cucchiara
In this paper we propose a deep architecture for detecting people attributes (e.g. gender, race, clothing ...) in surveillance contexts. Our proposal explicitly deal with poor reso…