Computer Vision Center (UAB)
He obtained his Ph.D. degree on action recognition at University of Barcelona (UB) in 2019. He is currently working on a multimodal fall detection project at Computer Vision Center (CVC), which is part of Universitat Autònoma de Barcelona (UAB). He is also a member of Human Pose Recovery and Behavior Analysis Group. He participated in the organization "Chalearn joint contest on multimedia challenges beyond visual analysis'' (ECCV16 and ICPR16), which included RGB-D gesture recognition and another track of personality traits recognition from short YouTube clips. His research interests include multimodality, action recognition, and sequential learning models.
Julio C.S. Jacques Junior
Computer Vision Center (UAB) and Open University of Catalonia
He received his MS degree in Applied Computing in 2006, from UNISINOS and his Ph.D. degree in Computer Science in 2012, from PUCRS, Brazil. Currently, he is a postdoctoral researcher at the Computer Science, Multimedia and Telecommunications department at Universitat Oberta de Catalunya (UOC), within the Scene Understanding and Artificial Intelligence (SUNAI) group. He is also a researcher collaborator 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 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 special attention to visual human behavior analysis.
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.
University of Barcelona, Barcelona, Spain
She is currently a double degree student of Mathematics and Computer Science at University of Barcelona. Her research interests include, between others, machine learning, computer vision, and complexity analysis.