My research interests lie at the intersection of Deep Learning, Computer Vision, 3D Geometry and their applications in Augmented Reality and Robotics. I enjoy studying how deep learning can be applied to computer vision problems including keypoint detection, image matching, relocalization, multi-view reconstruction, visual SLAM, depth estimation, homography estimation, camera calibration and bundle-adjustment.
Currently a researcher at Facebook Reality Labs Research (FRL Research). Previously I was a member of the AI Research Team at Magic Leap
I worked on developing new deep learning-based methods for Visual Simultaneous Localization and Mapping (Visual SLAM) and Structure-from-Motion (SfM). I was co-advised by Tomasz Malisiewicz
and Andrew Rabinovich
and authored publications at top-tier conferences including CVPR and RSS (e.g. Deep Homography Estimation, SuperPoint and SuperGlue). I also pioneered computer vision algorithms which were ultimately deployed on the ML1 headset.
Prior to Magic Leap, I received my Master's and Bachelor's degrees at the University of Michigan, where I studied Machine Learning, Computer Vision and Robotics. During my studies I worked on various small projects in areas such as person tracking, outdoor SLAM and 3D ConvNets.
Research Scientist at Facebook
Deep Learning, 3D Mapping
Lead Software Engineer at Magic Leap
Deep Learning, Visual SLAM, Mixed Reality
RGB-D SLAM, Augmented Reality
University of Michigan Master's Student
Computer Vision, Machine Learning, Robotics
University of Michigan Bachelors's Student
Robotics, Computer Science, International Studies
Published PyTorch code
for SuperGlue, includes live demo and easy-to-use evaluation code.
March 2020: SuperGlue: Learning Feature Matching with Graph Neural Networks
is accepted to CVPR 2020 as an Oral.
March 2019: Deep ChArUco: Dark ChArUco Marker Pose Estimation
is accepted to CVPR 2019.
Invited talk at Berkeley Artificial Intelligence Research Lab (BAIR)
Invited Keynote Talk
at the Bay Area Multimedia Forum Keynote (BAMMF) series in Palo Alto, CA.
Presented SuperPoint at ICVSS 2018
in stunning Sicily.
Published PyTorch code
for SuperPoint. Get up and running in 5 minutes or your money back!
SuperPoint selected as an oral
at the 1st International Workshop on Deep Learning for Visual SLAM
at CVPR in Salt Lake City.