How to caculate the gradient? Is there any formula for this?
Senbei
This process reminds me of the gradient descent.
I guess for doing this, we should carefully choose the step size or it will never converge.
And we also might need a proper threshod for judging wheather it is converged or not.
EmDeeZee
What is the convergence threshold? If it's too high, then you're not really converging to a point on the surface (instead converging to a point just off of it). If it's too low, it may take a lot longer to converge. How is this threshold chosen?
Zhuoqian
People are doing some research on a 3D data structure called "signed distance functions" which uses this idea. I first read about this in "DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation". https://arxiv.org/abs/1901.05103
How to caculate the gradient? Is there any formula for this?
This process reminds me of the gradient descent.
I guess for doing this, we should carefully choose the step size or it will never converge. And we also might need a proper threshod for judging wheather it is converged or not.
What is the convergence threshold? If it's too high, then you're not really converging to a point on the surface (instead converging to a point just off of it). If it's too low, it may take a lot longer to converge. How is this threshold chosen?
People are doing some research on a 3D data structure called "signed distance functions" which uses this idea. I first read about this in "DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation". https://arxiv.org/abs/1901.05103