: {f2D(I,N )}

→ O,
• PIFu∗
• PaMIR∗ : {f2D(I,N ), f3D(V)} → O,
• ICON : {N , γ(M)}
→ O,

where f2D denotes the 2D image encoder, f3D denotes the 3D
voxel encoder, V denotes the voxelized SMPL, O denotes
the entire predicted occupancy ﬁeld, and γ is the mesh-based
local feature extractor described in Sec. 3.2. The results are
summarized in Tab. 2-A, and discussed in Sec. 4.3-A. For
reference, we also report the performance of the original
PIFu [54], PIFuHD [55], and PaMIR [70]; our “simulated”
models perform well, and even outperform the original ones.

Renderp.

Train & Validation Sets
Twindom
AGORA

THuman

[3]
(cid:55)
(cid:55)
(cid:51)
(cid:55)
(cid:51)

[61]
(cid:55)
(cid:55)
(cid:51)
(cid:55)
(cid:51)

[47]
(cid:55)
(cid:55)
(cid:51)
(cid:51)
(cid:51)

[71]
(cid:51)
(cid:51)
(cid:55)
(cid:51)
(cid:55)

450 [54, 55]
375 [24]

1000 [70]

450 [IC]
3109 [IC†]

600 [IC†]
600 [70]

Free & public
Diverse poses
Diverse identities
SMPL(-X) poses
High-res texture

Number of scans

Test Set
ICON