It is ML in the sense of optimizing a nonconvex loss function over a dataset. It is not a fancy diffusion model or even a generative model, but it is no less a machine learning problem.
“Not ML” as in “not learning from data to apply in new situations” but rather they do “mathematical optimisation”.
The data they optimise over is just the images of the current camera trajectory (as far as I understand)
It seems to me they don't use any ML at all. They use backpropagation to jointly optimise the entire physics/motion model, which models camera motion and the generated blurry images (they generate multiple images for each camera frame along the path of motion of the camera, and then merge them, simulating motion blur)