Invited Speakers
Luca Carlone
Luca Carlone is the Charles Stark Draper Assistant Professor in the Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, and a Principal Investigator in LIDS. He received the PhD degree from the Polytechnic University of Turin, Turin, Italy, in 2012. From 2013 to 2015, he was a Post-Doctoral Fellow with the Georgia Institute of Technology, Atlanta, GA, USA. In 2015, he was a Post-Doctoral Associate with the Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology, Cambridge, MA, USA, where he became a Research Scientist in 2016. His research interests include nonlinear estimation, numerical and distributed optimization, and probabilistic inference, applied to sensing, perception, and decision-making in single- and multi-robot systems. He received the 2017 Transactions on Robotics King-Sun Fu Memorial Best Paper Award and the Best Paper Award at WAFR 2016.
Daniel Cremers
Daniel Cremers is the Chair of Computer Vision and Artificial Intelligence at the Technical University of Munich. His publications received several awards, including the 'Best Paper of the Year 2003' (Int. Pattern Recognition Society), the 'Olympus Award 2004' (German Soc. for Pattern Recognition) and the '2005 UCLA Chancellor's Award for Postdoctoral Research'. For pioneering research he received a Starting Grant (2009), two Proof of Concept Grants (2014 & 2018), a Consolidator Grant (2015) and an Advanced Grant (2020) by the European Research Council. Professor Cremers has served as associate editor for several journals including the International Journal of Computer Vision, the IEEE Transactions on Pattern Analysis and Machine Intelligence and the SIAM Journal of Imaging Sciences. He has served as area chair (associate editor) for ICCV, ECCV, CVPR, ACCV, IROS, etc, and as program chair for ACCV 2014. In 2018 he organized the largest ever European Conference on Computer Vision in Munich with 3300 delegates. He is member of the Bavarian Academy of Sciences and Humanities. He is honorary member of the Dagstuhl Scientific Directorate. On March 1st 2016, Prof. Cremers received the Gottfried Wilhelm Leibniz Award, the biggest award in German academia. He is co-founder of several companies, most recently the high-tech startup Artisense.
Andrew Davison
Andrew Davison hold the position of Professor of Robot Vision at the Department of Computing, Imperial College London, and lead the Dyson Robotics Laboratory at Imperial College where he is working on vision and AI technology for next generation home robotics. He also leads the Robot Vision Research Group though most of his activity is now within the Dyson Lab. Professor Davison is working in computer vision and robotics: specifically his main research has concerned SLAM (Simultaneous Localisation and Mapping) using vision, with a particular emphasis on methods that work in real-time with commodity cameras. He pioneered SLAM with vision from the mid 1990s onwards, and brought the SLAM acronym and methods from robotics to single camera computer vision with the breakthrough MonoSLAM algorithm in 2003 which enabled long-term, drift-free, real-time SLAM from a single camera for the first time, inspiring many researchers and industry developments in robotics and inside-out tracking for VR and AR.
Katerina Fragkiadaki
Katerina Fragkiadaki is an Assistant Professor in the Machine Learning Department in Carnegie Mellon University. She received her PhD from University of Pennsylvania in 2013 and was a postdoctoral fellow in UC Berkeley and Google research (2013-2016). She has done significant research on video segmentation, motion dynamics learning and on the area of injecting geometry into deep visual learning. Prof. Katerina Fragkiadaki’s group develops algorithms for mobile computer vision and learning of physics and common sense by watching and interacting with the world. She received a best PhD thesis award in 2013 and served as the area chair in CVPR 2018, ICML 2019, ICLR 2019.
Andreas Geiger
Andreas Geiger is a Professor of computer science heading the Autonomous Vision Group (AVG), University of Tübingen and the MPI for Intelligent Systems, Tübingen, Germany. From September 2016 to February 2018, he was a Visiting Professor in ETH Zurich. He received his PhD degree from Karlsruhe Institute of Technology in 2013. He is interested in 3D scene understanding, reconstruction, motion estimation, generative modeling and sensory-motor control in the context of autonomous systems. He and his team published the well-known KITTI dataset for autonomous driving.
Kristen Grauman
Kristen Grauman is a Professor in the Department of Computer Science at the University of Texas at Austin and a Research Scientist in Facebook AI Research (FAIR). Her research in computer vision and machine learning focuses on visual recognition and search. Before joining UT-Austin in 2007, she received her PhD at MIT. She is a AAAI Fellow, Sloan Fellow, a Microsoft Research New Faculty Fellow, and a recipient of NSF CAREER and ONR Young Investigator awards, the PAMI Young Researcher Award in 2013, the 2013 Computers and Thought Award from the International Joint Conference on Artificial Intelligence (IJCAI), the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2013, and the Helmholtz Prize (computer vision test of time award) in 2017. She was inducted into the UT Academy of Distinguished Teachers in 2017. She and her collaborators were recognized with the CVPR Best Student Paper Award in 2008 for their work on hashing algorithms for large-scale image retrieval, the Marr Prize at ICCV in 2011 for their work on modeling relative visual attributes, the ACCV Best Application Paper Award in 2016 for their work on automatic cinematography for 360 degree video, a Best Paper Honorable Mention at CHI in 2017 for work on crowds and visual question answering, and a Best Paper Finalist at CVPR 2019 for their work on 2.5D visual sound. She currently serves as an Associate Editor-in-Chief for the Transactions on Pattern Analysis and Machine Intelligence (PAMI) and as an Editorial Board member for the International Journal of Computer Vision (IJCV). She previously served as a Program Chair of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2015 and a Program Chair of Neural Information Processing Systems (NeurIPS) 2018.
Victor Adrian Prisacariu
Victor Adrian Prisacariu is an Associate Professor in Information Engineering with the Department of Engineering Science, University of Oxford, co-leading the Active Vision Lab and Chief Scientist of Niantic, Inc.. His current focus is on computer vision methods for real-time (semantic) AR on mobile and wearable platforms, but he also take san interest in other fields of computer vision and machine learning, such as quantization, one shot learning and network architecture search. Within the Active Vision Lab, he and his colleges work on computational vision, with an emphasis on 3D reconstruction and motion analysis, for applications in location and mapping, surveillance, wearable and assistive computing, augmented reality, navigation, and teleoperation. He co-founded 6D.ai, where they built APIs to help developers augment reality in ways that users would find meaningful, useful and exciting. The 6D.ai SDK used a standard built-in smartphone camera to build a cloud-based, crowdsourced three-dimensional semantic map of the world all in real-time, in the background. 6D.ai was aquired by Niantic in March 2020.
Shuxue Quan
Dr. Shuxue Quan is the director of research on computer vision and augmented reality at OPPO US Research Center where he leads team developing algorithms of SLAM, scene understanding, 3D reconstruction, human computer interaction and computational photography. His team also builds software framework and applications to enable AR on mobile devices and head mounted devices. Before OPPO, he worked at Qualcomm on computer vision, machine learning and mobile camera, after a few other positions at Sony, Micron and Broadcom. Dr. Quan received a PhD of Imaging Science from Rochester Institute of Technology, and MS and BS of Optical Engineering from Beijing Institute of Technology. Dr. Quan has been granted more than 40 international patents and published more than 20 journal or conference papers.
Pierre Moulon
Dr. Pierre Moulon is Principal Research Scientist at Zillow Group. He is the creator of OpenMVG (Multi-View Geometry), an open-source toolbox with state-of-the-art tools for structure-from-motion and 3D reconstruction. His strong belief in reproducible research drove him to develop the OpenMVG library. Pierre obtained his PhD in Computer Science from Universite Paris-Est, and was previously at Autodesk and Bentley Systems, where he worked on large scale 3D reconstruction. His primary research interests are image-based 3D modeling, multi-view geometry, and structure-from-motion. At Zillow, Pierre helped to develop the Zillow 3D Home® product, which is an immersive real estate visualization tool built around 360◦ imaging. His recent work includes 360 imaging for indoor reconstruction and the implementation of 360◦ structure-from-motion and multi-view-stereo in the OpenMVG/OpenMVS open source frameworks.
Jana Kosecka
Jana Kosecka (George Mason University) is a Professor at the Department of Computer Science, George Mason University. She is the recipient of David Marr's prize in Computer Vision and received the National Science Foundation CAREER Award. Jana is an Associate Editor of IEEE Robotics and Automation Letters, Member of the Editorial Board of International Journal of Computer Vision and Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence. She has numerous publications in refereed journals and conferences and is a co-author of a monograph titled Invitation to 3D vision: From Images to Geometric Models. Her general research interests are in Computer Vision and Robotics. In particular she is interested 'seeing' systems engaged in autonomous tasks, acquisition of static and dynamic models of environments by means of visual sensing, object recognition and human-computer interaction.
Simon Lucey
Simon Lucey is a Principal Scientist at Argo AI, and an Associate Research Professor in the Robotics Institute at Carnegie Mellon University, where he is part of the Computer Vision Group, and leader of the CI2CV Lab. He was a Principle Research Scientist at the CSIRO (Australia’s premiere government science organization) for 5 years. He received his PhD from Queensland University of Technology in 2003. His work includes training computers to extract geometric information from images and videos, novel approaches for applying vision and learning to embedded devices, and developing ways for computer systems to effectively read facial actions and body behavior.
Tomasz Malisiewicz
Tomasz Malisiewicz works as a Principal Engineer at Magic Leap’s Deep Learning team. He is the Co-Founder of VISION.AI, LLC. From August 2011 to September 2013, He was a Postdoctoral Fellow at MIT CSAIL, worked with Antonio Torralba. He received his PhD in Robotics from Carnegie Mellon University in 2011. He is broadly interested in computer vision, human vision, and machine learning. During his PhD, he was a recipient of the NSF Graduate Research Fellowship, spent two summers as an intern in Google Research, as well as one semester as a visiting student at École Normale Supérieure in Paris.
Deva Ramanan
Deva Ramanan is an Associate Professor at the Robotics Institute at Carnegie Mellon University and a Principle Scientist at Argo AI. Prior to joining CMU. He was an Associate Professor at UC Irvine. His research interests are computer vision and machine learning, with a focus on visual recognition. He was awarded the David Marr Prize in 2009, the PASCAL VOC Lifetime Achievement Prize in 2010, an NSF Career Award in 2010, the UCI Chancellor’s Award for Excellence in Undergraduate Research in 2011, the PAMI Young Researcher Award in 2012, one of Popular Science’s Brilliant 10 researchers in 2012, and the Longuet-Higgins Prize in 2018 for fundamental contributions in computer vision. His work is supported by NSF, ONR, DARPA, as well as industrial collaborations with Intel, Google, and Microsoft. He is on the editorial board of the International Journal of Computer Vision (IJCV) and is an associate editor for the IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI). He regularly serves as a senior program committee member for the IEEE Conference of Computer Vision and Pattern Recognition (CVPR), International Conference on Computer Vision (ICCV), and the European Conference on Computer Vision (ECCV). He served as program chair of CVPR 2018. He also regularly serves on NSF panels for computer vision and machine learning.
Raquel Urtasun
Raquel Urtasun is the Chief Scientist of Uber ATG and the Head of Uber ATG Toronto. She is also an Associate Professor in the Department of Computer Science at the University of Toronto, a Canada Research Chair in Machine Learning and Computer Vision and a co-founder of the Vector Institute for AI. Prior to this, she was an Assistant Professor at the Toyota Technological Institute at Chicago (TTIC), an academic computer science institute affiliated with the University of Chicago. She was also a visiting professor at ETH Zurich during the spring semester of 2010. She received her Ph.D. degree from the Computer Science department at Ecole Polytechnique Federal de Lausanne (EPFL) in 2006 and did her postdoc at MIT and UC Berkeley. She is a world leading expert in AI for self-driving cars. Her research interests include machine learning, computer vision, robotics and remote sensing. Her lab was selected as an NVIDIA NVAIL lab. She is a recipient of an NSERC EWR Steacie Award, an NVIDIA Pioneers of AI Award, a Ministry of Education and Innovation Early Researcher Award, three Google Faculty Research Awards, an Amazon Faculty Research Award, a Connaught New Researcher Award, a Fallona Family Research Award, an UPNA alumni award and two Best Paper Runner up Prize awarded at the Conference on Computer Vision and Pattern Recognition (CVPR) in 2013 and 2017 respectively. She was also named Chatelaine 2018 Woman of the year, and 2018 Toronto's top influencers by Adweek magazine.
Shichao Yang
Shichao Yang is a Research Scientist at Facebook Reality Labs from 2019. Before that, he received his PhD degree in Robotics in Carnegie Mellon University. His research focuses on the simultaneous localization and mapping (SLAM), visual-inertial odometry, semantic scene understanding, with application to AR/VR and robotics. He has published paper in top robotics conferences and journals, including TRO, JFR, ICRA, etc. He also interned at Facebook during his PhD studies.
Haibin Ling
Dr. Haibin Ling received B.S. and M.S. from Peking University in 1997 and 2000, respectively, and Ph.D. from University of Maryland in 2006. From 2000 to 2001, he was an assistant researcher at Microsoft Research Asia; from 2006 to 2007, he worked as a postdoctoral scientist at UCLA; from 2007-2008, he worked for Siemens Corporate Research as a research scientist; and from 2008 to 2019, he was a faculty member of the Department of Computer Sciences for Temple University. In fall 2019, he joined the Department of Computer Science of Stony Brook University, where he is now a SUNY Empire Innovation Professor. His research interests include computer vision, augmented reality, medical image analysis, visual privacy protection, and human computer interaction. He received Best Student Paper Award of ACM UIST in 2003 and NSF CAREER Award in 2014. He serves as associate editors for IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), Pattern Recognition (PR), and Computer Vision and Image Understanding (CVIU). He has served as Area Chairs various times for CVPR and ECCV.
Xiaoming Liu
Dr. Xiaoming Liu is an Associate Professor at the Department of Computer Science and Engineering of Michigan State University. He received the Ph.D. degree in Electrical and Computer Engineering from Carnegie Mellon University in 2004. Before joining MSU in Fall 2012, he was a research scientist at General Electric (GE) Global Research. His research interests include computer vision, machine learning, and biometrics. As a co-author, he is a recipient of Best Industry Related Paper Award runner-up at ICPR 2014, Best Student Paper Award at WACV 2012 and 2014, Best Poster Award at BMVC 2015, and Michigan State University College of Engineering Withrow Endowed Distinguished Scholar Award. He has been the Area Chair for numerous conferences, including FG, ICPR, WACV, ICIP, ICCV, and CVPR. He is the program co-chair of WACV 2018 and BTAS 2018. He is an Associate Editor of Neurocomputing, Pattern Recognition Letters, and Pattern Recognition. He has authored more than 100 scientific publications, and has filed 26 U.S. patents.
Yasuyuki Matsushita
Dr. Yasuyuki Matsushita received his B.S., M.S. and Ph.D. degrees in EECS from the University of Tokyo in 1998, 2000, and 2003, respectively. From April 2003 to March 2015, he was with Visual Computing group at Microsoft Research Asia. In April 2015, he joined Osaka University as a professor. His research area includes computer vision, machine learning and optimization. He is an Editor-in-Chief of International Journal of Computer Vision (IJCV) and is/was on editorial board of IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), The Visual Computer journal, IPSJ Transactions on Computer Vision Applications (CVA), and Encyclopedia of Computer Vision. He served/is serving as a Program Co-Chair of PSIVT 2010, 3DIMPVT 2011, ACCV 2012, ICCV 2017, and a General Co-Chair for ACCV 2014 and ICCV 2021. He is a senior member of IEEE.
Jingyi Yu
Dr. Jingyi Yu is executive dean in the School of Information Science and Technology at ShanghaiTech University. He received B.S. from Caltech in 2000 and Ph.D. from MIT in 2005. He is also affiliated with the University of Delaware. His research interests span a range of topics in computer vision and computer graphics, especially on computational photography and non-conventional optics and camera designs. He has published over 120 papers at highly refereed conferences and journals including over 70 papers at the premiere conferences and journals CVPR/ICCV/ECCV/TPAMI. He has also been granted 10 US patents. His research has been generously supported by the National Science Foundation (NSF), the National Institute of Health, the Army Research Office, and the Air Force Office of Scientific Research (AFOSR). He is a recipient of the NSF CAREER Award, the AFOSR YIP Award, and the Outstanding Junior Faculty Award at the University of Delaware. He has served as general chair, program chair, and area chair of many international conferences such as CVPR, ICCV, ECCV, ICCP and NIPS. He is currently an Associate Editor of IEEE TPAMI, IEEE TIP and Elsevier CVIU, and will be program chair of ICPR 2020 and IEEE CVPR 2021.