where K(θ, ψ, β, t) are the predicted 2D keypoints from FLAME pose, expression and shape parameters θ, ψ, β and global
translation t, and K target are the optimization targets predicted by [6]. We use one single shape parameter β for each subject.
During optimization, we regularize shape and expression by:

Ekp =(cid:13)(cid:13)K(θ, ψ, β, t) − K target(cid:13)(cid:13)2 ,

Ereg = λβ (cid:107)β(cid:107)2

2 +

λψ
T

(cid:107)ψτ(cid:107)2
2 ,

(cid:88)

τ∈[0,T ]

where β and ψ are the shape and expression parameters, T is the number of frames, and λβ and λψ are objective weights, set
to 1e − 4 and 2e − 4, respectively. We also leverage temporal consistency terms for expression, pose and global translations:

(λtemp

ψ

(cid:107)ψτ +1 − ψτ(cid:107)2

2 + λtemp

θ

(cid:107)θτ +1 − θτ(cid:107)2

2 + λtemp

t

(cid:107)tτ +1 − tτ(cid:107)2
2),

(1)

(cid:88)

Etemp =

1

T − 1

τ∈[0,T−1]
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