Machines Can See is an international summit in Russia bringing together the leading minds of AI to share latest ideas and trends in Computer Vision and Machine Learning.
The main goal of the event is to strengthen the interaction between Russian and international AI communities in the field of Computer Vision and Machine Learning and to exchange the knowledge and expertise.
Date: 25 june
PhD. Leading entrepreneur and researcher in computer vision and machine learning. He founded and still runs (CEO of) the most popular computer vision library in the world: OpenCV.
He organized the computer vision team for Stanley, the autonomous car that won the $2M DARPA Grand Challenge which in turn kicked off the autonomous driving industry. Gary served as a visiting Professor at Stanford University Computer Science department for seven years. He helped develop one of the first Video Search startups, VideoSurf, that sold to Microsoft in 2011. He founded Industrial Perception Inc. which sold to Google in 2013 and he created the Silicon Valley office of Magic Leap. He serves on the boards and advisory boards of over a dozen startups. Currently, he is Co-founder/CTO of Arraiy.com located in Palo Alto.
Partner scientist at Microsoft in Cambridge, UK.
He has published numerous highly-cited papers, and received many awards for his work, including ten “best paper” prizes at various venues, the Silver medal of the Royal Academy of Engineering, and the BCS Roger Needham award. He is a fellow of the Royal Academy of Engineering, the British Computer Society, and the International Association for Pattern Recognition. He received PhD from the University of Edinburgh and then moved to Oxford in 1996. He spent several years as a Royal Society University Research Fellow before joining Microsoft in 2005. He loves programming, particularly in C++, and his recent work has included new numerical algorithms for Eigen, and compilation of F# to C.
Senior Lecturer in the Department of Computer Science of University College London and CEO of Ariel AI.
His research interests are at the intersection of computer vision and deep learning, aiming at the development of models that unify problems of structured prediction and shape modeling with deep learning, as well as multi-task learning. He publishes and reviews regularly in the major computer vision conferences (CVPR,ICCV,ECCV), he has served multiple times as Area Chair and has been an Associate Editor for CVIU and IVC. Prior to UCL and Ariel AI he was a Research Scientist at Facebook AI Research (FAIR) as well as a faculty and researcher at CentraleSupelec
Director of Science leading the Microsoft Mixed Reality and Artificial Intelligence lab in Zurich and a Professor of Computer Science at ETH Zurich.
Marc is best known for his work in 3D computer vision, but also works on robotics, graphics and machine learning. Most recently he is focused on combining 3D reconstruction with semantic scene understanding. He has received several prizes for his research, including a Marr prize, an NSF CAREER award, a Packard Fellowship and an ERC starting grant. He has published over 300 peer-reviewed scientific publications and holds multiple patents. He was a general chair for ECCV 2014, program chair for CVPR 2009 and he will serve as a general chair for ICCV 2019.
Senior Research Scientist at Google Brain.
After graduating from the Moscow State University he was a postdoc at the University of Freiburg working on self-supervised learning, image generation as well as motion and 3D structure estimation (FlowNet, DeMoN). In 2017 he joined Intel Visual Computing Lab and worked on applications of deep learning to sensorimotor control, including autonomous driving (CARLA simulator) and robotics (drone racing, learning to walk). Since April 2019 he is with Google Brain in Berlin. His current research interests are focused on learning representations for downstream tasks such as recognition or control.
Research scientist at Facebook AI Research (FAIR) since 2015.
After graduating from Ecole Normale Superieure de Cachan, he received a PhD (2005) from the University of Rennes for his thesis on error-resilient compression and joint source channel coding. After PhD he focused his research on computer vision and pattern recognition. He joined INRIA as a permanent researcher in 2006, where he was leading several projects on large image and video collections. He joined Facebook AI Research in 2015, where he currently serves as site lead of the Paris laboratory. He has received an ERC grant in 2013 and the Koenderink test of time award in 2018.
Allen E. Puckett Professor of Electrical engineering at Caltech.
Pietro Perona received his PhD from UC Berkeley, was a post-doctoral fellow at MIT and is now the Allen E. Puckett Professor of Electrical Engineering at the California Institute of Technology in Pasadena. He is interested in visual categorization and in the analysis of behavior. He has worked on partial differential equations for image processing, on modeling visual perception, on visual search and attention and on the role of visual mechanisms in art production and perception.
Poster and demo session
9:45 — 10:20 AM
10:20 — 10:30 AM
10:30 AM — 12:00 PM
Challenge results and prizes
12:00 AM — 12:30 PM
Poster and Demo sessions
12:00 AM — 2:00 PM
2:00 — 4:00 PM
4:00 — 4:30 PM
4:30 — 5:50 PM
5:50 — 6:10 PM
6:10 —7:30 PM
Samsung & Skoltech
Head of Graphics & Media Lab
Head of Samsung-HSE lab