Computer Vision and Deep Learning Summit

July 8, 2021

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The fifth annual international summit ‘Machines Can See’ was held by VisionLabs on July 8 2021.

Each year summit brings together the world's leading experts in computer vision and machine learning to discuss technology trends and share experience. MCS 2021 was focused on human-centric technologies based on analysis of person's attributes without collecting and analyzing personal data.

MCS 2017

MCS 2018

MCS 2019

MCS 2020

Invited speakers

Dima Damen

University of Bristol

Dima Damen is Associate Professor in the Department of Computer Science at the University of Bristol, focusing her research interests in the automatic understanding of object interactions, actions and activities using wearable visual (and depth) sensors. She has contributed to novel research directions including assessing action completion, skill/expertise determination from video sequences, discovering task-relevant objects, dual-domain and dual-time learning as well as multi-modal fusion using vision, audio and language. Dima received her PhD from the University of Leeds in 2009. She has received multiple distinctions including Outstanding Reviewer awards at CVPR 2020 and ICCV 2017.

Ira Kemelmacher-Shlizerman

University of Washington; UW Reality Lab; Google

Ira Kemelmacher-Shlizerman is an Associate Professor of Computer Science at the Allen School, Director of the UW Reality Lab, and an Eng Lead at Google. Her reserch is focused on computer vision, computer graphics, deep learning, audio and AR/VR. Prof. Kemelmacher-Shlizerman holds a PhD in Computer Science and Applied Mathematics from the Weizmann Institute of Science. In 2016 she founded and was the CEO of startup Dreambit acquired by Facebook. She has received several distinctions including the Google faculty award and the Madrona prize.

Efstratios Gavves

University of Amsterdam

Efstratios Gavves is an Associate Professor with the University of Amsterdam, Scientific Director of the QUVA Deep Vision Lab between the University of Amsterdam and Qualcomm, Scientific Director of the POP-AART Lab between the University of Amsterdam, the Netherlands Cancer Institute (NKI), and Elekta. He co-founded Ellogon.AI, a University spinoff and in collaboration with NKI, with the mission of using AI for pathology and genomics. His research is focused on Temporal Machine Learning , Efficient Computer Vision, and Machine Learning for Oncology. Efstratios has been awarded ERC Career Starting Grant in 2020.

Kris Kitani

Carnegie Mellon University

Kris M. Kitani is an associate research professor and director of the MS in Computer Vision program of the Robotics Institute at Carnegie Mellon University. He received his BS at the University of Southern California and his MS and PhD at the University of Tokyo. His research projects span the areas of computer vision, machine learning and human computer interaction. In particular, his research interests lie at the intersection of first-person vision, human activity modeling and inverse reinforcement learning. He received several awards and distictions including Marr Prize honorable mention at ICCV 2017 and best paper honorable mention ECCV 2012.

Bernard S. Ghanem

King Abdullah University of Science and Technology

Bernard Ghanem is an Associate Professor in the CEMSE division, a theme leader at the Visual Computing Center (VCC), and the Interim Lead of the AI Initiative at KAUST. His research interests lie in computer vision and machine learning with emphasis on topics in video understanding, 3D recognition, and theoretical foundations of deep learning. He has co-authored more than 120 research papers in his field as well as three issued patents. His work has received several awards and honors, including Best Paper Awards at workshops at CVPR 2013, CVPR 2019, ECCV 2018 and ECCV 2020.

The summit included a computer vision competition on gesture recognition. The winners were awarded with the prize fund of 750 000 rubles and special presents by Intel.

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The participation in the summit is free but a registration is required. If you plan to join on-site, please come in advance to allow enough time for check-in that might be longer than usual due COVID-19 circumstances.