Deep Learning Based Inertial Tracking: Publications

Journal papers

• [1]

  GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks

  Y. Almalioglu M. R. U. Saputra P. P. de Gusmao A. Markham and N. Trigoni

  In IEEE International Conference on Robotics and Automation (ICRA). 2019.

  Details about GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks | BibTeX data for GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks | Download  (pdf) of GANVO: Unsupervised Deep Monocular Visual Odometry and Depth Estimation with Generative Adversarial Networks

Conference papers

• [1]

  MotionTransformer: Transferring Neural Inertial Tracking Between Domains

  Changhao Chen‚ Yishu Miao‚ Chris Xiaoxuan Lu‚ Linhai Xie‚ Phil Blunsom‚ Andrew Markham and Niki Trigoni

  In The Thirty−Third AAAI Conference on Artificial Intelligence (AAAI−19). 2019.

  Details about MotionTransformer: Transferring Neural Inertial Tracking Between Domains | BibTeX data for MotionTransformer: Transferring Neural Inertial Tracking Between Domains | Download  (pdf) of MotionTransformer: Transferring Neural Inertial Tracking Between Domains

• [2]

  Transferring Physical Motion Between Domains for Neural Inertial Tracking

  Changhao Chen‚ Yishu Miao‚ Chris Xiaoxuan Lu‚ Phil Blunsom‚ Andrew Markham and Niki Trigoni

  In NIPS 2018 workshop on Modelling the Physical world: Perception‚ Learning and Control. 2018.

  Details about Transferring Physical Motion Between Domains for Neural Inertial Tracking | BibTeX data for Transferring Physical Motion Between Domains for Neural Inertial Tracking | Download  (pdf) of Transferring Physical Motion Between Domains for Neural Inertial Tracking