Machines Can See 2020

About

Machines Can See is an international summit bringing together the leading minds of AI to share latest ideas and trends in Computer Vision and Machine Learning.

This year MCS summit will go fully online to reach
the maximum audience during the COVID-19 period.
As in previous years, we are dedicated to share
knowledge and will present the latest technological
advances in Computer Vision and AI while providing
a platform for discussion, innovation and networking.

The 4th MCS 2020 summit will feature scientific and applied talks by top speakers from academia and industry.
 Four evenings of the summit will include scientific talks, a panel session and thematic discussions.

PlayVideo

Speakers

Deva Ramanan

Deva Ramanan

CMU / Argo AI

Deva Ramanan is an associate professor at the Robotics Institute at Carnegie Mellon University, a principle scientist at Argo AI, and the director of the CMU Argo AI Center for Autonomous Vehicle Research. Prior to joining CMU, he was an associate professor at UC Irvine. His research interests span 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 IEEE PAMI Young Researcher Award in 2012, was named one of Popular Science's Brilliant 10 researchers in 2012, was named a National Academy of Sciences Kavli Fellow in 2013, and won the Longuet-Higgins Prize in 2018 for fundamental contributions in computer vision. He is an associate editor of IJCV and PAMI and a regular area chair of CVPR, ICCV and ECCV.

Cordelia Schmid

Cordelia Schmid

INRIA / Google

Cordelia Schmid holds a permanent researcher position at Inria since 1997, where she is a research director. Starting 2018 she has a joint appointment with Google research. She has published more than 300 articles, mainly in computer vision. She has been editor-in-chief for IJCV (2013--2018), a program chair of IEEE CVPR 2005 and ECCV 2012 as well as a general chair of IEEE CVPR 2015, ECCV 2020 and ICCV 2023. In 2006, 2014 and 2016, she was awarded the Longuet-Higgins prize for fundamental contributions in computer vision that have withstood the test of time. She is a fellow of IEEE. She was awarded an ERC advanced grant in 2013, the Humbolt research award in 2015 and the Inria & French Academy of Science Grand Prix in 2016. She was elected to the German National Academy of Sciences, Leopoldina, in 2017. In 2018 she received the Koenderink prize for fundamental contributions in computer vision. She received the Royal Society Milner award in 2020.

Vladlen Koltun is the Chief Scientist for Intelligent Systems at Intel. He directs the Intelligent Systems Lab, which conducts high-impact basic research in computer vision, machine learning, robotics, and related areas. He has mentored more than 50 PhD students, postdocs, research scientists, and PhD student interns, many of whom are now successful research leaders.

Jitendra Malik

Jitendra Malik

Berkeley / Facebook

Jitendra Malik is Arthur J. Chick Professor in the Department of Electrical Engineering and Computer Sciences. at the University of California at Berkeley and a Research Director of Facebook AI Research in Menlo Park. Jitendra's group has worked on computer vision, computational modeling of biological vision, computer graphics and machine learning. Several well-known concepts and algorithms arose in this work, such as anisotropic diffusion, normalized cuts, high dynamic range imaging, shape contexts and R-CNN. His publications have received numerous best paper awards, including five test of time awards - the Longuet-Higgins Prize for papers published at CVPR (twice) and the Helmholtz Prize for papers published at ICCV (three times). He received the 2013 IEEE PAMI-TC Distinguished Researcher in Computer Vision Award, the 2014 K.S. Fu Prize from the International Association of Pattern Recognition, the 2016 ACM-AAAI Allen Newell Award, the 2018 IJCAI Award for Research Excellence in AI, and the 2019 IEEE Computer Society Computer Pioneer Award.

Josef Sivic

Josef Sivic

INRIA / CTU

Josef Sivic is a senior researcher at Inria in Paris and a distinguished senior researcher at the Czech Institute of Robotics, Informatics and Cybernetics at the Czech Technical University in Prague. He received the habilitation degree from Ecole Normale Superieure in Paris in 2014, PhD from the University of Oxford in 2006 and MSc degree from Czech Technical University in 2002. Before joining Inria he was a post-doctoral associate at the Computer Science and Artificial Intelligence Lab at the Massachusetts Institute of Technology. He received the British Machine Vision Association Sullivan Thesis Prize, three test-of-time awards at major computer vision conferences (1x CVPR, 2x ICCV), and an ERC Starting Grant. He is a chair at the Paris AI Research Institute.

Laurens van der Maaten is a Research Director at Facebook AI Research (FAIR). He leads FAIR’s New York site. His research focuses on machine learning and computer vision. Before, he worked as an Assistant Professor (with tenure) at Delft University of Technology, as a post-doctoral researcher at UC San Diego, and as a Ph.D. student at Tilburg University. He is interested in a variety of topics in machine learning and computer vision. Currently, he is working on embedding models, large-scale weakly supervised learning, visual reasoning, and cost-sensitive learning. (CVPR's second Best Paper Award went to Gao Huang, Zhuang Liu, Laurens van der Maaten and Kilian Q. Weinberger for their research on "Densely Connected Convolutional Networks." Research for the paper was conducted by Cornell University in collaboration with Tsinghua University and Facebook AI Research.

James Hays

James Hays

Georgia Tech / Argo AI

James Hays is an associate professor of computing at Georgia Institute of Technology and Principal Scientist at Argo AI. Previously, he was the Manning assistant professor of computer science at Brown University. James received his Ph.D. from Carnegie Mellon University and was a postdoc at Massachusetts Institute of Technology. His research interests span computer vision, computer graphics, robotics, and machine learning. His research often involves exploiting non-traditional data sources (e.g. internet imagery, crowdsourced annotations, thermal imagery, human sketches, autonomous vehicle sensor data) to explore new research problems (e.g. global geolocalization, sketch to real, hand-object contact prediction). James is the recipient of an NSF CAREER Award and Sloan Fellowship.

Manohar Paluri

Manohar Paluri is the Director of Artificial Intelligence at Facebook, managing the computer vision efforts on the applied side. His team focuses on pushing the boundaries in computer vision with an eye towards forwarding Facebook's mission to connect people. The team is at the intersection of research and product and is excited about building experiences for the billions of people who use Facebook. Paluri's interests and experience spans computer vision, robotics, and machine learning. Before starting at Facebook as a Computer Vision Researcher in August of 2012, Paluri worked at Google, IBM, and Stanford Research Institute and was in the Ph.D. program at Georgia Tech. Paluri also holds a master's degree in computer science from Georgia Tech, as well as a bachelor's degree in computer vision from the International Institute of Information Technology, Hyderabad.

Yaser Sheikh

Yaser Sheikh

CMU / Facebook

Yaser Sheikh direct the Facebook Reality Lab in Pittsburgh focused on achieving photorealistic telepresence. He is also an associate professor (on leave) at Carnegie Mellon University. His research is broadly focused on machine perception and rendering of social behavior, spanning sub-disciplines in computer vision, computer graphics, and machine learning. He is an associate editor of PAMI and has served on the technical committees of SIGGRAPH, CVPR, and ICCV. He has won Popular Science’s Best of What’s New Award, the Honda Initiation Award (2010), best paper awards at WACV (2012), SAP (2012), SCA (2010), and ICCV THEMIS (2009), best student paper award at CVPR (2018), best demo award at ECCV 2016, and won the MSCOCO Keypoint Challenge (2016). His research has been featured by various media outlets including The New York Times, The Verge, Popular Science, BBC, MSNBC, New Scientist, slashdot, and WIRED.

Victor Lempitsky

Victor Lempitsky

Samsung / Skoltech

Victor Lempitsky leads the Samsung AI Center in Moscow as well as the Vision, Learning, Telepresence (VIOLET) Lab at this center. He is also an associate professor at Skolkovo Institute of Science and Technology (Skoltech). In the past, Victor was a researcher at Yandex, at the Visual Geometry Group (VGG) of Oxford University, and at the Computer Vision group of Microsoft Research Cambridge. He has a PhD ("kandidat nauk") degree from Moscow State University (2007). Victor's research interests are in various aspects of computer vision and deep learning, in particular, generative deep learning. He has served as an area chair for top computer vision and machine learning conferences (CVPR, ICCV, ECCV, ICLR, NeurIPS) on multiple occasions. His recent work on neural head avatars was recognized as the most-discussed research publication of 2019 by Altmetric Top 100 rating.

Artem Babenko

Artem Babenko received his PhD degree in computer science from Moscow Institute of Physics and Technology (MIPT) in 2017. Currently, he works at Yandex Research and supervises MS and PhD students from the joint Yandex-MIPT and Yandex-HSE labs. Artem is the author of numerous papers at top-tier venues, such as CVPR, ICCV, ECCV, NeurIPS, ICML. He has also been a member of program committees of these conferences and was the Outstanding Reviewer of CVPR 2018. His scientific interests include runtime-efficient and memory-efficient methods in large-scale computer vision and unsupervised learning for visual understanding.

Abhinav Gupta

Abhinav Gupta

CMU / Facebook

Abhinav Gupta is an Associate Professor at the Robotics Institute, Carnegie Mellon University and Research Manager at Facebook AI Research (FAIR). Abhinav's research focuses on scaling up learning by building self-supervised, lifelong and interactive learning systems. Specifically, he is interested in how self-supervised systems can effectively use data to learn visual representation, common sense and representation for actions in robots. Abhinav is a recipient of several awards including ONR Young Investigator Award, PAMI Young Research Award, Sloan Research Fellowship, Okawa Foundation Grant, Bosch Young Faculty Fellowship, YPO Fellowship, IJCAI Early Career Spotlight, ICRA Best Student Paper award, and the ECCV Best Paper Runner-up Award. His research has also been featured in Newsweek, BBC, Wall Street Journal, Wired and Slashdot.

Schedule

Deva Ramanan

Embodied perception in-the-wild

18:30 — 19:00 MSK
17:30 — 18:00 CET
08:30 — 09:00 PDT

Cordelia Schmid

Automatic video understanding

19:00 — 19:30 MSK
18:00 — 18:30 CET
09:00 — 09:30 PDT

Vladlen Koltun

Machines that see in the real world

19:30 — 20:00 MSK
18:30 — 19:00 CET
09:30 — 10:00 PDT

Jitendra Malik

TBD

20:00 — 20:30 MSK
19:00 — 19:30 CET
10:00 — 10:30 PDT

Discussion

Deva Ramanan, Cordelia Schmid, Vladen Koltun, Jitendra Malik. Moderator: Ivan Laptev.

20:30 — 21:15 MSK
19:30 — 20:15 CET
10:30 — 11:15 PDT

Josef Sivic

Weakly supervised learning for visual recognition

19:00 — 19:30 MSK
18:00 — 18:30 CET
09:00 — 09:30 PDT

Laurens van der Maaten

From Visual Recognition to Visual Understanding

19:30 — 20:00 MSK
18:30 — 19:00 CET
09:30 — 10:00 PDT

James Hays

Thermal imaging for grasp understanding

20:00 — 20:30 MSK
19:00 — 19:30 CET
10:00 — 10:30 PDT

Discussion

Josef Sivic, Laurens van der Maaten, James Hays. Moderator: Manohar Paluri.

20:30 — 21:15 MSK
19:30 — 20:15 CET
10:30 — 11:15 PDT

Yaser Sheikh

Photorealistic Telepresence

18:30 — 19:00 MSK
17:30 — 18:00 CET
08:30 — 09:00 PDT

Victor Lempisky

Neural image generation

19:00 — 19:30 MSK
18:00 — 18:30 CET
09:00 — 09:30 PDT

Artem Babenko

Unsupervised Discovery of Interpretable Directions in the GAN Latent Space

19:30 — 20:00 MSK
18:30 — 19:00 CET
09:30 — 10:00 PDT

Abhinav Gupta

Towards self-supervised curious robots

20:00 — 20:30 MSK
19:00 — 19:30 CET
10:00 — 10:30 PDT

Discussion

Yaser Sheikh, Victor Lempisky, Artem Babenko, Abhinav Gupta. Moderator: Ivan Laptev.

20:30 — 21:15 MSK
19:30 — 20:15 CET
10:30 — 11:15 PDT

Info partners

Community partners

Partner

Join in!

subscribe to the news