  Hand modeling is critical for immersive VR/AR, action understanding, or human
healthcare. Existing parametric models account only for hand shape, pose, or
texture, without modeling the anatomical attributes like bone, which is
essential for realistic hand biomechanics analysis. In this paper, we present
PIANO, the first parametric bone model of human hands from MRI data. Our PIANO
model is biologically correct, simple to animate, and differentiable, achieving
more anatomically precise modeling of the inner hand kinematic structure in a
data-driven manner than the traditional hand models based on the outer surface
only. Furthermore, our PIANO model can be applied in neural network layers to
enable training with a fine-grained semantic loss, which opens up the new task
of data-driven fine-grained hand bone anatomic and semantic understanding from
MRI or even RGB images. We make our model publicly available.
