Canonical volume: We represent the canonical volume
Fc as a continuous field with an MLP that outputs color c
and density σ given a point x:

Fc(x) = MLPθc(γ(x)),

(3)

where γ is a sinusoidal positional encoding defined as
(x, sin(20πx), cos(20πx), ..., sin(2L−1πx), cos(2L−1πx))
and L is a hyper-parameter that determines the number of
frequency bands [41].

Skeletal motion: Following Weng et al. [69], we com-
pute the skeletal deformation Tskel as a kind of inverse, lin-
ear blend skinning that maps points in the observation space

K(cid:88)

i=1

Tskel(x, p) =

wi

o(x)(Rix + ti),

(4)

(cid:80)K

wi
k=1 wk

o is the blend weight for the i-th bone and Ri, ti
where wi
are the rotation and translation, respectively, that map the
bone’s coordinates from observation to canonical space; Ri
and ti can be explicitly computed from p (see supplemen-
o.
tary). We then aim to optimize for wi
by storing K blend weights as a set of volumes {wi
from which the observation weights are derived as:
HumanNeRF- Free-viewpoint Rendering of Moving People from Monocular Video