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With the success of deep learning based approaches in tackling challenging problems in computer vision, a wide range of deep architectures have recently been proposed for the task of visual odometry (VO) estimation.
Long short-term memory, 1995
S. Hochreiter and J. Schmidhuber · 1995
Earlier work this paper cites.
Are we ready for autonomous driving? the kitti vision benchmark suite
A. Geiger, P. Lenz, and R. Urtasun · 2012
Earlier work this paper cites.
Real-time rgb-d camera relocalization
B. Glocker, S. Izadi, J. Shotton, and A. Criminisi · 2013
Earlier work this paper cites.
SVO: Fast semi-direct monocular visual odometry
C. Forster, M. Pizzoli, and D. Scaramuzza · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Earlier work this paper cites.
Dropout: A simple way to prevent neural networks from overfitting
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov · 2014
Earlier work this paper cites.
Flownet: Learning optical flow with convolutional networks
A. Dosovitskiy, P. Fischer, E. Ilg, P. Häusser, C. Hazırbaş, V. Golkov, P. v.d. Smagt, D. Cremers, and T. Brox · 2015
Earlier work this paper cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
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Cited alongside, same era.
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Later among the works it cites.
Demon: Depth and motion network for learning monocular stereo
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Later among the works it cites.
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S. Vijayanarasimhan, S. Ricco, C. Schmid, R. Sukthankar, and K. Fragkiadaki · 2017
Later among the works it cites.
Deepvo: Towards end-to-end visual odometry with deep recurrent convolutional neural networks
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Later among the works it cites.
Unsupervised learning of depth and ego-motion from video
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Later among the works it cites.
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S. Lowry, N. Sünderhauf, P. Newman, J. J. Leonard, D. Cox, P. Corke, and M. J. Milford · 2016
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Vinet: Visual-inertial odometry as a sequence-to-sequence learning problem
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End-to-end, sequence-to-sequence probabilistic visual odometry through deep neural networks
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UnDeepVO: Monocular visual odometry through unsupervised deep learning
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