Skip to content
VidLoc: A Deep Spatio-Temporal Model for 6-DoF Video-Clip Relocalization, Geometric loss functions for camera pose regression with deep learning, PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
log
.gitignore
LICENSE
README.md
data.py
net_builder.py
run_posenet.py

README.md

Deep Camera Relocalization

Getting Started

  • Download the Cambridge Landmarks King's College dataset from here.

  • Download the starting and trained weights from here.

  • To run:

    • Extract the King's College dataset to wherever you prefer
    • Extract the starting and trained weights to wherever you prefer
    • If you want to retrain, simply run train.py
    • If you just want to test, simply run test.py

References

Ronald Clark, Sen Wang, Andrew Markham, Niki Trigoni, Hongkai Wen. VidLoc: A Deep Spatio-Temporal Model for 6-DoF Video-Clip Relocalization. CVPR 2017.

Alex Kendall and Roberto Cipolla. Geometric loss functions for camera pose regression with deep learning. CVPR, 2017.

Alex Kendall, Matthew Grimes and Roberto Cipolla. PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization. ICCV, 2015.

Acknowledgement

Original implementation of PoseNet: https://github.com/kentsommer/tensorflow-posenet

You can’t perform that action at this time.