DeepFusion: real-time dense 3D reconstruction for monocular SLAM using single-view depth and gradient predictions (bibtex)

by T Laidlow, J Czarnowski and S Leutenegger

Reference:

DeepFusion: real-time dense 3D reconstruction for monocular SLAM using single-view depth and gradient predictions (T Laidlow, J Czarnowski and S Leutenegger), In 2019 International Conference on Robotics and Automation (ICRA), 2019.

Bibtex Entry:

@inproceedings{laidlow2019deepfusion,
 title = {DeepFusion: real-time dense 3D reconstruction for monocular SLAM using single-view depth and gradient predictions},
 author = {T Laidlow and J Czarnowski and S Leutenegger},
 booktitle = {2019 International Conference on Robotics and Automation (ICRA)},
 pages = {4068--4074},
 year = {2019},
 organization = {IEEE},
}

by T Laidlow, J Czarnowski and S Leutenegger

Reference:

Bibtex Entry:

@inproceedings{laidlow2019deepfusion,
 title = {DeepFusion: real-time dense 3D reconstruction for monocular SLAM using single-view depth and gradient predictions},
 author = {T Laidlow and J Czarnowski and S Leutenegger},
 booktitle = {2019 International Conference on Robotics and Automation (ICRA)},
 pages = {4068--4074},
 year = {2019},
 organization = {IEEE},
}

Hanzhi Chen

PhD StudentTechnical University of Munich

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

Office: 03.09.041
Mail: Hanzhi.Chen@tum.de

Personal Website | Google Scholar | LinkedIn | GitHub

😎 Brief Bio

I am a PhD student in the Smart Robotics Lab of Technical University of Munich with Prof. Stefan Leutenegger. Previously, I received my M.Sc. degree in Robotics, Cognition, Intelligence with high distinction from Technical University of Munich.

🤖 Research Interest

Object-Centric Perception (to understand objects' geometry, concepts, affordance, and more)
Neural Scene Representations (to facilitate object-centric perception)
Few-Shot Imitation Learning (to connect embodiments' learning through object-centric representations)

🤓 Student Projects

I am always happy to work with cool folks with passion and talents. You can check my previous research works to see if there is a match between us. If you want to work with me, shoot me an email with your up-to-date transcript, résumé, and a brief comment about what research topic really interests you! This paper collection about neural fields for robotics might be helpful for you as a starting point to get inspired :)

Please refrain from inquiring me about supervision for external thesis by non-academic institutions or bachelor thesis, thank you!