Our paper, “Global Deconvolutional Networks for Semantic Segmentation” written by Vladimir, Janghoon and Jaesik is accepted BMVC-16. We show¬†that simple but innovative ways to incorporate global context information to improve deep learning based semantic segmentation. We also demonstrate that the proposed method achieve comparative performance (74.0%) in the PASCAL VOC (VOC2012) data set.