Self-Supervised 3D Vision


Is one eye all you need? Can we learn robot perception from raw videos only? Can we get robust 3D depth estimation from a single monocular camera? In this talk, we will discuss recent research progress we made at TRI on self-supervised learning for 3D vision, its uses, limitations, and promising future directions combining self-supervision with other scalable sources of supervision like simulation.


Rareș Ambruș is a Senior Research Scientist and Tech Lead in the Machine Learning team at the Toyota Research Institute (TRI), in Los Altos, CA, USA. His research interests lie at the intersection of robotics, computer vision and machine learning, with an emphasis on self-supervised learning for 3D perception. He received his PhD in 2017 from the Royal Institute of Technology (KTH), Sweden focusing on self-supervised perception and mapping for mobile robots. He has 8+ years of industry experience working on autonomous vehicles, mobile robots and virtual/augmented reality and has more than 25 publications and patents in top-tier computer vision, machine learning and robotics conferences.

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