Is anybody aware of any recent machine learning work in 3d object composition space? In particular, I often waste a lot of time manually finding parameters that work for a particular system and it seems like if I just had a differentiable system for working with things like 3d primitives (spheres, cylinders, etc) I'd be able to explore that space with constraints efficiently.