Sergio Escalera

Computer Vision Center (UAB) and University of Barcelona, Spain

Sergio Escalera obtained the P.h.D. degree on Multi-class visual categorization systems at Computer Vision Center, UAB. He obtained the 2008 best Thesis award on Computer Science at Universitat Autònoma de Barcelona. He is ICREA Academia. He leads the Human Pose Recovery and Behavior Analysis Group at UB, CVC, and the Barcelona Graduate School of Mathematics. He is an associate professor at the Department of Mathematics and Informatics, Universitat de Barcelona. He is an adjunct professor at Universitat Oberta de Catalunya, Aalborg University, and Dalhousie University. He has been visiting professor at TU Delft and Aalborg Universities. He is a member of the Visual and Computational Learning consolidated research group of Catalonia. He is also a member of the Computer Vision Center at UAB. He is series editor of The Springer Series on Challenges in Machine Learning. He is vice-president of ChaLearn Challenges in Machine Learning, leading ChaLearn Looking at People events. He is co-creator of Codalab open source platform for challenges organization. He is also member of ELLIS, the AERFAI Spanish Association on Pattern Recognition, ACIA Catalan Association of Artificial Intelligence, INNS, and Chair of IAPR TC-12: Multimedia and visual information systems. He has different patents and registered models. He has published more than 250 research papers and participated in the organization of scientific events, including CCIA04, ICCV11, CCIA14, AMDO16, FG17, NIPS17, NIPS18, FG19, and workshops at ICCV, ICMI, ECCV, CVPR, ICPR, NIPS. He has been guest editor at JMLR, TPAMI, IJCV, TAC, PR, MVA, JIVP, Expert Systems, and Neural Comp. and App. He has been General co-Chair of FG20, Area Chair at WACV16, NIPS16, AVSS17, FG17, ICCV17, WACV18, FG18, BMVC18, NIPS18, FG19, BMVC19, ICIAP21 and Competition and Demo Chair at FG17, NIPS17, NIPS18, ECMLPKDD19 and FG19. His research interests include automatic analysis of humans from visual and multi-modal data, with special interest in inclusive, transparent, and fair affective computing and people characterization: personality and psychological profile computing.

Rama Chellappa

University of Maryland, United States of America

is a distinguished University Professor at University of Maryland. He holds a Minta Martin Professorship in the A.J. Clark School of Engineering and served as the Chair of the Electrical and Computer Engineering Department from 2011-2018. He has coauthored and coedited books on MRFs, face and gait recognition and collected works on image processing and analysis. He has organized tens of events and has been general co-chair of CVPR and FG, among others.

Eduard Vazquez

Anyvision, Belfast, Northern Ireland

has been working on Computer Vision for the last 15 years. Former lecturer of Artificial Intelligence, he has 10 years’ experience on commercialising a variety of methods for medical imaging, retail, manufacturing, public safety, health and safety and real-time video analytics. His main focus has been to understand the gap between theory and the real world in order to help delivering products that can be effectively adopted. He is Research Technical Manager at AnyVision, working on face recognition for multiple use cases and industries and in-store analytics for retail, from cloud to edge.

Neil Robertson

Queen’s University Belfast / Anyvision, Belfast, Northern Ireland

Neil is Professor of Research (Vision Systems) and Director of Research for the Data Science Centre at Queen’s University Belfast. He researches new underpinning machine learning methods for visual analytics, and his principal research focus is activity recognition in real video. He started his career in the UK Scientific Civil Service with DERA (2000-2002) and QinetiQ (2002-2007) and was the 1851 Royal Commission Fellow at Oxford University (2003–2006). His machine learning and vision research is extensive. He is technical co-founder of two successful computer vision companies which have attracted large investment. He is the founding CTO of AnyVision.

Sankha Subhra Mukherjee

Anyvision, Belfast, Northern Ireland

did his PhD in deep learning for social signal processing from Edinburgh. He is a co-founder and executive vice-president research at AnyVision in Belfast NI. He has been working and publishing machine learning research since 2011. Dr. Mukherjee was the recipient of numerous awards for research, including the University Post Graduate Research Prize from Heriot-Watt University and the Techtop 2009 award from Techtop, India. His main research interests include multimodal machine learning and deep learning, bayesian optimisation and uncertainty.

Pau Buch-Cardona

Computer Vision Center (UAB) and University of Barcelona, Spain

obtained his Master's degree on Telecommunications Engineering at Universitat Autònoma de Barcelona in 2013. He is currently working on a European project in healthcare for elderly. He is also a member of Human Pose Recovery and Behavior Analysis Group at UB, CVC. His research interests include multimodality, deep learning interpretability and AI for health.

Tomas Sixta

Anyvision, Belfast, Northern Ireland

received his PhD degree in AI and biocybernetics from the Faculty of Electrical Engineering, Czech Technical University in Prague, Czech Republic, in 2019. He is currently a researcher at AnyVision. His research interests include face recognition and algorithmic fairness.

Julio C. S. Jacques Junior

Universitat Oberta de Catalunya (UOC) and Computer Vision Center (CVC/UAB), Spain

received his Ph.D. degree in Computer Science from PUCRS in 2012, Brazil. Currently, he is a postdoctoral researcher at the Computer Science, Multimedia and Telecommunications department at Universitat Oberta de Catalunya (UOC). He collaborates within the Computer Vision Center (CVC) and Human Pose Recovery and Behavior Analysis (HUPBA) group at Universitat Autònoma de Barcelona (UAB) and University of Barcelona (UB), as well as within ChaLearn (LAP) Looking at People. He also have collaborated with the organization of some workshops and challenges organized by ChaLearn LAP (ECCV’16, ICPR’16, CVPR/IJCNN’17, NeurIPS'19). His research interests include, between others, computer vision-based applications with a particular focus on visual human behaviour analysis.


100% online

ECCV 2020 is going ahead and will be a 100% online event. Technically, a unified platform is being decided by ECCV organizers and will be communicated soon.

ECCV 2020

ChaLearn Looking at People workshop on Fair Face Recognition and Analysis and associated Challenge.