Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry (bibtex)
by N. Yang, R. Wang, J. Stueckler and D. Cremers
Reference:
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry (N. Yang, R. Wang, J. Stueckler and D. Cremers), In European Conference on Computer Vision (ECCV), 2018. ([arxiv],[supplementary],[project])
Bibtex Entry:
@string{eccv="European Conference on Computer Vision (ECCV)"}
@inproceedings{yang2018dvso,
 author = {N. Yang and R. Wang and J. Stueckler and D. Cremers},
 title = {Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry},
 booktitle = {European Conference on Computer Vision (ECCV)},
 year = {2018},
 month = {September},
 award = {Oral Presentation},
 keywords = {dso, dvso, deep learning, monocular depth estimation, semi-supervised learning, slam, visual odometry, vslam},
}
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Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry (bibtex)
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry (bibtex)
by N. Yang, R. Wang, J. Stueckler and D. Cremers
Reference:
Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry (N. Yang, R. Wang, J. Stueckler and D. Cremers), In European Conference on Computer Vision (ECCV), 2018. ([arxiv],[supplementary],[project])
Bibtex Entry:
@string{eccv="European Conference on Computer Vision (ECCV)"}
@inproceedings{yang2018dvso,
 author = {N. Yang and R. Wang and J. Stueckler and D. Cremers},
 title = {Deep Virtual Stereo Odometry: Leveraging Deep Depth Prediction for Monocular Direct Sparse Odometry},
 booktitle = {European Conference on Computer Vision (ECCV)},
 year = {2018},
 month = {September},
 award = {Oral Presentation},
 keywords = {dso, dvso, deep learning, monocular depth estimation, semi-supervised learning, slam, visual odometry, vslam},
}
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members:yangn

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Nan Yang

PhD student

Technical University of Munich

School of Computation, Information and Technology
Informatics 9
Boltzmannstrasse 3
85748 Garching
Germany

Fax: +49-89-289-17757
Office: 
Mail: yangn@in.tum.de

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Research Interests

My research interests lie in incorporating deep learning into classical visual odometry and SLAM.

Brief Bio

Nan Yang received his Bachelor's degree in Computer Science from Beijing University of Posts and Telecommunications and his Master's degree in Informatics from the Technical University of Munich. Since May 2018, he is a Ph.D. student and senior computer vision researcher in Artisense, a startup co-founded by Prof. Daniel Cremers.

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