  In this paper, we present a new network named Attention Aware Network (AASeg)
for real time semantic image segmentation. Our network incorporates spatial and
channel information using Spatial Attention (SA) and Channel Attention (CA)
modules respectively. It also uses dense local multi-scale context information
using Multi Scale Context (MSC) module. The feature maps are concatenated
individually to produce the final segmentation map. We demonstrate the
effectiveness of our method using a comprehensive analysis, quantitative
experimental results and ablation study using Cityscapes, ADE20K and Camvid
datasets. Our network performs better than most previous architectures with a
74.4\% Mean IOU on Cityscapes test dataset while running at 202.7 FPS.
