So, in essence, this network can learn to "unproject" images.
Since projection is a lossy operation, a projected image has potentially multiple inverses. And this makes me wonder how this system deals with the situation where two or more inverses exist and are equally likely.
Since projection is a lossy operation, a projected image has potentially multiple inverses. And this makes me wonder how this system deals with the situation where two or more inverses exist and are equally likely.