The project provides a deep learning methodology for computing semantically segmented bird’s eye view images from multiple vehicle-mounted cameras. It combines Inverse Perspective Mapping (IPM) with deep neural networks to transform camera perspectives, enabling automated vehicles to perceive their environment more accurately from a top-down view. The approach is designed to bridge the sim2real gap for autonomous driving perception systems.