no code implementations • 28 Oct 2020 • Divya Kanapram, Damian Campo, Mohamad Baydoun, Lucio Marcenaro, Eliane L. Bodanese, Carlo Regazzoni, Mario Marchese
The proposed method produces multiple inference models by considering several features of the observed data.
no code implementations • 2 Jun 2020 • Damian Campo, Giulia Slavic, Mohamad Baydoun, Lucio Marcenaro, Carlo Regazzoni
This paper proposes a method for performing continual learning of predictive models that facilitate the inference of future frames in video sequences.
no code implementations • 17 Mar 2020 • Giulia Slavic, Damian Campo, Mohamad Baydoun, Pablo Marin, David Martin, Lucio Marcenaro, Carlo Regazzoni
This paper proposes a method for detecting anomalies in video data.
no code implementations • 9 Sep 2019 • Damian Campo, Alejandro Betancourt, Lucio Marcenaro, Carlo Regazzoni
This paper presents a methodology that aims at the incremental representation of areas inside environments in terms of attractive forces.
no code implementations • 9 Sep 2019 • Damian Campo, Vahid Bastani, Lucio Marcenaro, Carlo Regazzoni
This work proposes a novel method for estimating the influence that unknown static objects might have over mobile agents.
no code implementations • 3 Sep 2019 • Vahid Bastani, Damian Campo, Lucio Marcenaro, Carlo S. Regazzoni
A method for online identification of group of moving objects in the video is proposed in this paper.
no code implementations • 8 Jun 2018 • Mahdyar Ravanbakhsh, Mohamad Baydoun, Damian Campo, Pablo Marin, David Martin, Lucio Marcenaro, Carlo S. Regazzoni
In this work, a hierarchical model is introduced by means of a cross-modal Generative Adversarial Networks (GANs) processing high dimensional visual data.
no code implementations • 7 Jun 2018 • Mahdyar Ravanbakhsh, Mohamad Baydoun, Damian Campo, Pablo Marin, David Martin, Lucio Marcenaro, Carlo S. Regazzoni
This paper presents a novel approach for learning self-awareness models for autonomous vehicles.
no code implementations • 17 Mar 2018 • Mohamad Baydoun, Mahdyar Ravanbakhsh, Damian Campo, Pablo Marin, David Martin, Lucio Marcenaro, Andrea Cavallaro, Carlo S. Regazzoni
This paper focuses on multi-sensor anomaly detection for moving cognitive agents using both external and private first-person visual observations.