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8 changes: 4 additions & 4 deletions README.rst
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@@ -1,7 +1,7 @@
RayNet
======

This python pachage provides the code that accompanies our CVPR 2018 paper with
This python package provides the code that accompanies our CVPR 2018 paper with
title **RayNet: Learning Volumetric 3D Reconstruction with Ray Potentials**.

.. image:: http://raynet-mvs.com/site/raynet_teaser.png
Expand Down Expand Up @@ -29,9 +29,9 @@ install :-)

Depending on how you want to use our code, there are two alternatives regarding
installation. You can either use a package manager or download and install the
library manually. For those who just want to use the library we recommend to
library manually. For those who just want to use the library, we recommend to
directly install the latest version from *PyPI*, whereas for those who want to
be able to edit the code we recommend to install the library manually.
be able to edit the code, we recommend to install the library manually.


* *Install from Pypi with:*
Expand Down Expand Up @@ -86,7 +86,7 @@ Below we list some papers that are relevant to the provided code.

Citation
--------
If you are using our code, please cite `our paper <http://openaccess.thecvf.com/content_cvpr_2018/papers/Paschalidou_RayNet_Learning_Volumetric_CVPR_2018_paper.pdf>`__.The BibTeX reference is::
If you are using our code, please cite `our paper <http://openaccess.thecvf.com/content_cvpr_2018/papers/Paschalidou_RayNet_Learning_Volumetric_CVPR_2018_paper.pdf>`__. The BibTeX reference is::

@InProceedings{Paschalidou_2018_CVPR,
author = {Paschalidou, Despoina and Ulusoy, Osman and Schmitt, Carolin and Van Gool, Luc and Geiger, Andreas},
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