> But NNs give the possibility of gathering much more information from recognizing objects. Information that Lidar systems don't have. Wouldn't you feed both t

> But NNs give the possibility of gathering much more information from recognizing objects. Information that Lidar systems don't have. Wouldn't you feed both the depth map from the lidar and imagery from the cameras into the neural network? I imagine that a variety of different sensors as input would make it easier to do classification. As an analogy, someone who has lost their sense of smell might have a harder time telling the difference between a clean sock and a dirty sock than I would. Please let me know if I'm wrong here, but I assume that the depth information that can be derived from parallax is not a superset of what you get from lidar (I'm thinking about low light, glare, objects with complicated geometries, similar-colored objects obscuring each other, etc).