on Deep Learning for Computer Vision

Open Lectures by Guest Speakers

This Summer School will include two open talks from on Aula Master of A3 building in Campus Nord UPC (directions). This session will be open to the general public.

Kevin McGuinness

Dr Kevin McGuinness is an Assistant Professor and Science Foundation Ireland Funded Starting Investigator with the School of Electronic Engineering in Dublin City University. He also works very closely with the Insight Centre for Data Analytics. He finished my B.Sc (Hons) in Computer Applications and Software Engineering in Dublin City University in 2005 and was awarded a Ph.D. from the School of Electronic Engineering in 2009. He has since been a postdoctoral researcher at the CLARITY Centre for Sensor Web Technologies, and a research fellow at the Insight Centre for Data Analytics. His primary research interests are computer vision, deep learning, image and video segmentation, segmentation evaluation, machine learning, content-based multimedia information retrieval, and human-computer interaction.

Talk - Crowd counting and analysis: Understanding images containing medium to large groups of people is becoming an increasingly important application of computer vision. Stadiums, airports, concerts, and cities, routinely facilitate large crowds and need to handle the corresponding safety and logistical issues that arise. Crowded images bring their own particular challenges and many approaches have been proposed for counting, density estimation, behaviour classification, and anomaly detection. This talk will focus on our recent work in Insight/DCU on crowded scene analysis and on how we use deep learning, multi-task learning, and domain adaptation for counting and analysing crowds. I will also describe our 2018 CVPR paper that describes how counting models can be adapted across domains, which allows counting of penguins, cells, cars, and people using a model with 95% shared parameters.

     

Laura Leal-Taixé

Prof. Laura Leal-Taixé is leading the Dynamic Vision and Learning group at the Technical University of Munich, Germany. She received her Bachelor and Master degrees in Telecommunications Engineering from the Technical University of Catalonia (UPC), Barcelona. She did her Master Thesis at Northeastern University, Boston, USA and received her PhD degree (Dr.-Ing.) from the Leibniz University Hannover, Germany. During her PhD she did a one-year visit at the Vision Lab at the University of Michigan, USA. She also spent two years as a postdoc at the Institute of Geodesy and Photogrammetry of ETH Zurich, Switzerland and one year at the Technical University of Munich. In 2017, she won the Sofja Kovalevskaja Award of 1.65 million euros from the presitgious Humboldt Foundation for her project “socialMaps”. Her research interests are dynamic scene understanding, in particular multiple object tracking and segmentation, as well as machine learning for video analysis.