Learning lane geometry by aerial and ground perspectives

A method for lane detection, the method comprises:

• (a) determining, by a lane detection neural network (NN) and based on locations of one or more road lanes within an aerial image, locations of the one or more road lanes on a ground-vehicle-acquired (GVA) image;
• and
• (b) responding to the determining of the locations of the one or more road lanes on the GVA image;
• wherein the lane detection NN was trained to perform aerial-images-to-GVA-images conversion;
• wherein the aerial image was generated, by a first NN, based in the GVA image:
• wherein the first NN was trained to perform GVA-images-to-aerial-images conversion;
• wherein the GVA image was acquired by a two dimensional camera of a ground vehicle;
• and
• wherein the locations of the one or more road lanes within the aerial image are provided by a second NN that was trained to perform lane detection in arial images.

A non-transitory computer readable medium for lane detection, the non-transitory computer readable medium stores instructions for:

• determining, by a lane detection neural network (NN) and based on locations of one or more road lanes within an aerial image, locations of the one or more road lanes on a ground-vehicle-acquired (GVA) image;
• and
• responding to the determining of the locations of the one or more road lanes on the GVA image;
• wherein the lane detection NN was trained to perform aerial-images-to-GVA-images conversion;
• wherein the aerial image was generated, by a first NN, based in the GVA image;
• wherein the first NN was trained to perform GVA-images-to-aerial-images conversion;
• wherein the GVA image was acquired by a two dimensional camera of a ground vehicle;
• and
• wherein the locations of the one or more road lanes within the aerial image are provided by a second NN that was trained to perform lane detection in arial images.