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We present a robust and real-time monocular six degree of freedom visual relocalization system.
Transforming neural-net output levels to probability distributions
John Denker and Yann Lecun · 1991
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David JC MacKay · 1992
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Distinctive image features from scale-invariant keypoints
David G Lowe · 2004
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Probabilistic robotics
Sebastian Thrun, Wolfram Burgard, and Dieter Fox · 2005
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Variational inference for dirichlet process mixtures
David M Blei and Michael I Jordan · 2006
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FAB-MAP: Probabilistic localization and mapping in the space of appearance
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DTAM: Dense tracking and mapping in real-time
Richard A Newcombe, Steven J Lovegrove, and Andrew J Davison · 2011
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Practical variational inference for neural networks
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Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Scene coordinate regression forests for camera relocalization in RGB-D images
Jamie Shotton, Ben Glocker, Christopher Zach, Shahram Izadi, Antonio Criminisi, and Andrew Fitzgibbon · 2013
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Jakob Engel, Thomas Schöps, and Daniel Cremers · 2014
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Matthew D Zeiler and Rob Fergus · 2014
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Bolei Zhou, Agata Lapedriza, Jianxiong Xiao, Antonio Torralba, and Aude Oliva · 2014
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How transferable are features in deep neural networks?
Jason Yosinski, Jeff Clune, Yoshua Bengio, and Hod Lipson · 2014
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Place recognition with convnet landmarks: Viewpoint-robust, condition-robust, training-free
Niko Sunderhauf, Sareh Shirazi, Adam Jacobson, Feras Dayoub, Edward Pepperell, Ben Upcroft, and Michael Milford · 2015
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Convolutional networks for real-time 6-dof camera relocalization
Alex Kendall, Matthew Grimes, and Roberto Cipolla · 2015
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Orb-slam: a versatile and accurate monocular slam system
Raul Mur-Artal, JMM Montiel, and Juan D Tardos · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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