In this thesis, a pipeline is created consisting of two parts. In the first part, the moving objects (cars, cyclists, pedestrians) are detected in street-view imagery using image segmentation neural networks and a LIDAR-based moving object detection approach. In the second part, those moving objects are deleted from the image data and an image inpainting approach is used to inpaint the hole. This is a unique approach in which information from multiple views is used as an input for a Generative Adversarial Network (GAN).