VIBE VS HierarchicalProbabilistic3DHuman

there are projects like this and similar, that are able to create motion capture from video: https://github.com/KevinLTT/video2bvh or https://github.com/mkocabas/VIBE

Another Edit: Here's another one that supports FBX export out of the box: https://github.com/mkocabas/VIBE

Github

Code for https://arxiv.org/abs/2110.00990 found: https://github.com/akashsengupta1997/HierarchicalProbabilistic3DHuman

I don't know of one yet. Lot of people are working on it, using various strategies. The grail being able to provide a virtual fitting-room experience. Or monitoring fitness of individuals.

A 2021 paper with code (I haven't tried it): https://github.com/akashsengupta1997/hierarchicalprobabilist... to generate a 3d morph-able human-shape in the correct pose from a single picture.

A picture always has scale uncertainty (a 2-meter human viewed from 1 meter away look the same that a 1-meter human viewed from 0.5 meter away), so that is an additional problem that must be taken care of.

But now recent phone have 3d sensor that provide information that could be useful.

To generate 3d human models there is also makehuman . In the old days there was a soft called facegen, that could generate 3d face models and could automatically fit their parameters to two pictures using an iterating refinement procedure.

Deep-learning usually estimate everything jointly in a single step so they are faster, but often less accurate. But there exist models that learn to refine a previously generated model, so you can apply them repeatedly and get improved quality (Denoising Diffusion Probabilistic Models is one generic class of models that does this).

Nevertheless, I find that reading a few related work sections of new papers gives me a good idea about the seminal papers in a field, since they will be repeatedly cited. Here is shameless self-plug to something I worked on: https://github.com/akashsengupta1997/HierarchicalProbabilistic3DHuman. I am not really a big name researcher and this paper probably won't be super impactful, so feel free to ignore the method, but I would recommend reading the related work section since it lists some of the impactful papers from good researchers. (Also check out related work sections from other papers to cross-reference).