Why would you want to guess at a 3d mapping from a 2d image when you can get 3d data directly from a sensor, like lidar? Getting 3d from 2d images is certainly

Why would you want to guess at a 3d mapping from a 2d image when you can get 3d data directly from a sensor, like lidar? Getting 3d from 2d images is certainly interesting and will have its applications. It's less accurate and more computationally demanding than using 3d input directly, however. Cars can and should have more than 2d input. The point of the article is that using a diverse array of sensors in cars will help the algorithm make better predictions. There are many edge cases out there that aren't covered,and we shouldn't expect engineers to plan for them all. What we want to do is throw a lot of raw input at an algorithm and run it through a ton of simulations. All steps of this are non-trivial, but with more data, it is easier.