4.4 Texture Inference
Following the practice of Texture Field [58] and PIFu [8], we
also regard the surface texture as a vector function deﬁned
in the space near the surface, which can support texturing
of shapes with arbitrary topology and self-occlusion. To per-
form texture inference, we make some simple modiﬁcation
to our network. Speciﬁcally, we deﬁne the output of the
decoder in Fig.2 as an RGBα vector ﬁeld instead of a scalar
ﬁeld. The RGB value is the network prediction of the color of
a speciﬁc point on the mesh surface, while the alpha channel
is used to blend the predicted value with the observed one:

C(pi) = α ∗ S (I, π(p)) + (1 − α) ∗ C(cid:48)(pi)

(13)
where C(cid:48)(pi) is the color prediction provided by the net-
work, i.e., the ﬁrst three channels of the decoder output, α
is the last channel of the decoder output and C(pi) is the
ﬁnal color prediction. Thus, the reconstruction loss in Eqn.6
is modiﬁed accordingly to:
LR =
PaMIR- Parametric Model-Conditioned Implicit Representation for Image-based Human Reconstruction