README.md edited online with Bitbucket

Author: gpapan

README.md

@@ -10,21 +10,21 @@ This distribution provides a publicly available implementation for the key model
 It also contains implementations for methods supporting model learning using only weakly labeled examples, described in a second follow-up [arXiv paper](http://arxiv.org/abs/1502.02734).
 Please consult and consider citing the following papers:
 
-   @inproceedings{chen2014semantic,
-     title={Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs},
-     author={Liang-Chieh Chen and George Papandreou and Iasonas Kokkinos and Kevin Murphy and Alan L Yuille},
-     booktitle={ICLR},
-     url={http://arxiv.org/abs/1412.7062},
-     year={2014}
-   }
-
-   @inproceedings{papandreou15,
-     title={Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation},
-     author={George Papandreou and Liang-Chieh Chen and Kevin Murphy and Alan L Yuille},
-     url={http://arxiv.org/abs/1502.02734},
-     year={2015}
-   }
+    @inproceedings{chen2014semantic,
+      title={Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs},
+      author={Liang-Chieh Chen and George Papandreou and Iasonas Kokkinos and Kevin Murphy and Alan L Yuille},
+      booktitle={ICLR},
+      url={http://arxiv.org/abs/1412.7062},
+      year={2014}
+    }
+
+    @inproceedings{papandreou15,
+      title={Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation},
+      author={George Papandreou and Liang-Chieh Chen and Kevin Murphy and Alan L Yuille},
+      url={http://arxiv.org/abs/1502.02734},
+      year={2015}
+    }
 
 ### Performance
 
-At the time of its release, DeepLab is the state-of-art method on semantic image segmentation on the challenging PASCAL VOC-2012 image segmentation task, with the latest variant achieving 72.7% mean IoU on the test set -- see the [leaderboard](http://host.robots.ox.ac.uk:8080/leaderboard/displaylb.php?challengeid=11&compid=6).
+At the time of its release, DeepLab is the state-of-art method on semantic image segmentation on the challenging PASCAL VOC-2012 image segmentation task, with the latest variant achieving 72.7% mean IoU on the test set -- see the [leaderboard](http://host.robots.ox.ac.uk:8080/leaderboard/displaylb.php?challengeid=11&compid=6).