A two-stream conditional generative adversarial network for improving semantic predictions in urban driving scenes

Fahad Lateef, Mohamed Kas, Abderrazak Chahi, Yassine Ruichek

Abstract: Highlights•Explores various post-processing techniques for enhancing semantic segmentation.•Novel Two-Stream Conditional GAN enhances urban drive scene segmentation.•Enhances feature extraction by implementing dynamic weighting within streams.•Evaluates the model against existing semantic segmentation methodologies.•Tests on Cityscapes, Mapillary, BDD100K reveal major IoU gains with proposed model.