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Andrew Rabinovich
Researcher at Google
Publications - 67
Citations - 51886
Andrew Rabinovich is an academic researcher from Google. The author has contributed to research in topics: Convolutional neural network & Artificial neural network. The author has an hindex of 28, co-authored 67 publications receiving 37872 citations. Previous affiliations of Andrew Rabinovich include University of California, San Diego & Discovery Institute.
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DeepPerimeter: Indoor Boundary Estimation from Posed Monocular Sequences
TL;DR: This work presents DeepPerimeter, a deep learning based pipeline for inferring a full indoor perimeter from a sequence of posed RGB images, which results in excellent visual and quantitative performance on the popular ScanNet and FloorNet datasets and works for room shapes of various complexities as well as in multiroom scenarios.
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Self-informed neural network structure learning
TL;DR: This paper proposed a method for augmenting a trained neural network classifier with auxiliary capacity in a manner designed to significantly improve upon an already well-performing model, while minimally impacting its computational footprint.
Patent
Method and system for performing simultaneous localization and mapping using convolutional image transformation
TL;DR: In this paper, a neural network is trained by generating a plurality of points, determining a 3D trajectory, sampling the 3D trajectories to obtain camera poses viewing the points, projecting the points onto 2D planes, comparing a generated homography using the projected points to the ground-truth homography and modifying the neural network based on the comparison.
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EyeNet: A Multi-Task Network for Off-Axis Eye Gaze Estimation and User Understanding
Zhengyang Wu,Srivignesh Rajendran,Tarrence van As,Joelle Zimmermann,Vijay Badrinarayanan,Andrew Rabinovich +5 more
TL;DR: EyeNet is presented, the first single deep neural network which solves multiple heterogeneous tasks related to eye gaze estimation and semantic user understanding for an off-axis camera setting.
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MagicEyes: A Large Scale Eye Gaze Estimation Dataset for Mixed Reality.
Zhengyang Wu,Srivignesh Rajendran,Tarrence van As,Joelle Zimmermann,Vijay Badrinarayanan,Andrew Rabinovich +5 more
TL;DR: This work presents MagicEyes, the first large scale eye dataset collected using real MR devices with comprehensive ground truth labeling and proposes a new multi-task EyeNet model designed for detecting the cornea, glints and pupil along with eye segmentation in a single forward pass.