barvin04 / BPnP

Back-propagatable PnP

This repo provides the code used in the paper

End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization (CVPR 2020)

Watch our video demo

Install

bash requirements.sh

Back-propagatable PnP (BPnP)

Using BPnP is easy. Just add the following line in your code

import BPnP
bpnp = BPnP.BPnP.apply

Then you can use it as any autograd function in Pytorch.

Demo experiments

To see the demos presented in the paper, run

python demoPoseEst.py

or

python demoSfM.py

or

python demoCamCali.py

Cite this work

@inproceedings{BPnP2020,
    Author = {Chen, Bo and Parra, Alvaro and Cao, Jiewei and Li, Nan and Chin, Tat-Jun},
    Title = {End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization},
    Booktitle = {CVPR},
    Year = {2020}}