Semantic segmentation is a challenging problem due to pixel level annotations requirement. Deep Convolutional Neural Networks (DCNNs) are performing with tremendous results on Semantic Segmentation problem but there are still limitation of training data for real-time applications. Domain Adaptation of Semantic segmentation tries to adapt the target domain data distribution without knowing labels to effectively do semantic segmentation in real-time scenarios. Generative adversarial Networks are also incorporated to learn the distribution of both the source and target data simultaneously and minimize their difference.