Upgrades to the 6DoF object tracker presented in : "A Framework for Evaluating 6-DOF Object Trackers" [arxiv paper].
The original code release can be found at this website.
The dataset can be downloaded at this website.
The bb3d parameter is used for depth values clipping, detailed in Charles Renaud's thesis (under review).
The newbg3 parameter is used for the background values augmentation scheme, detailed in Charles Renaud's thesis (under review).
Includes the fpnet architecture from FoundationPose.
To train the network, version 0.1 of pytorch_toolbox is required.
Other dependencies are listed in requirements.txt
If you use this dataset in your research, please cite:
@inproceedings{garon2018framework,
title={A framework for evaluating 6-dof object trackers},
author={Garon, Mathieu and Laurendeau, Denis and Lalonde, Jean-Fran{\c{c}}ois},
booktitle={Proceedings of the European Conference on Computer Vision (ECCV)},
pages={582--597},
year={2018}
}
Change the parameters in generator_script.sh and run to generate the training and validation dataset.
Change the parameters in train_script.sh and run to train the network.
License for Non-Commercial Use
If this software is redistributed, this license must be included.
The term software includes any source files, documentation, executables,
models, and data.
This software is available for general use by academic or non-profit,
or government-sponsored researchers. This license does not grant the
right to use this software or any derivation of it for commercial activities.
For commercial use, please contact Jean-Francois Lalonde at Université Laval
at jflalonde@gel.ulaval.ca.
This software comes with no warranty or guarantee of any kind. By using this
software, the user accepts full liability.