  KBody is a method for fitting a low-dimensional body model to an image. It
follows a predict-and-optimize approach, relying on data-driven model estimates
for the constraints that will be used to solve for the body's parameters.
Acknowledging the importance of high quality correspondences, it leverages
``virtual joints" to improve fitting performance, disentangles the optimization
between the pose and shape parameters, and integrates asymmetric distance
fields to strike a balance in terms of pose and shape capturing capacity, as
well as pixel alignment. We also show that generative model inversion offers a
strong appearance prior that can be used to complete partial human images and
used as a building block for generalized and robust monocular body fitting.
Project page: https://zokin.github.io/KBody.
