• Publications
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Optimizing the Viewing Graph for Structure-from-Motion
TLDR
We propose a novel optimization that improves the quality of the relative geometries in the viewing graph by enforcing loop consistency constraints with the epipolar point transfer. Expand
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HIPI : A Hadoop Image Processing Interface for Image-based MapReduce Tasks
TLDR
The amount of images being uploaded to the internet is rapidly increasing, with Facebook users uploading over 2.5 billion new photos every month [Facebook 2010], however, applications that make use of this data are severely lacking. Expand
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Theia: A Fast and Scalable Structure-from-Motion Library
TLDR
In this paper, we have presented a comprehensive multi-view geometry library, Theia, that focuses on large-scale SfM. Expand
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Solving for Relative Pose with a Partially Known Rotation is a Quadratic Eigenvalue Problem
TLDR
We propose a novel formulation of minimal case solutions for determining relative pose of perspective and generalized cameras given a partially known rotation, namely, a known axis of rotation. Expand
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StereoDRNet: Dilated Residual StereoNet
TLDR
We propose a system that uses a convolution neural network to estimate depth from a stereo pair followed by volumetric fusion of the predicted depth maps to produce a 3D reconstruction of a scene. Expand
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Live tracking and mapping from both general and rotation-only camera motion
TLDR
An approach to real-time tracking and mapping that supports any type of camera motion in 3D environments, that is, general (parallax-inducing) as well as rotation-only (degenerate) motions. Expand
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gDLS: A Scalable Solution to the Generalized Pose and Scale Problem
TLDR
In this work, we present a scalable least-squares solution for computing a seven degree-of-freedom similarity transform for multiple cameras. Expand
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Large Scale SfM with the Distributed Camera Model
TLDR
We introduce the distributed camera model, a novel model for Structure-from-Motion (SfM). Expand
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On Sampling Focal Length Values to Solve the Absolute Pose Problem
TLDR
In this paper, we challenge the notion that using minimal solvers is always optimal and propose to compute the pose for a camera with unknown focal length by randomly sampling a focal length value. Expand
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SlimNets: An Exploration of Deep Model Compression and Acceleration
TLDR
We show that by combining pruning and knowledge distillation methods we can create a compressed network 85 times smaller than the original, all while retaining 96% of the original model's accuracy. Expand
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