For the sequential model rgb-to-normal, conditioning on
the separately generated normal maps, the generated color
images exhibit color aberrations in comparison to the in-
put image, as shown in (c) of Figure 7. Conversely, for the
sequential model normal-to-rgb, conditioning on the sepa-
rately generated color images, the normal maps give unrea-
sonable geometry, as illustrated in (d) of Figure 7. These ex-
periments demonstrate that jointly predicting normal maps
and color images through the cross-domain attention mech-
anism can facilitate a comprehensive perception of informa-
tion from different domains. We also speculate that in the
context of sequential models, the generated color images or
normal maps of stage 1 may exhibit a minor domain gap to
the ground truth data trained in stage 2. Therefore, com-
pared to sequential prediction, the cross-domain approach

Figure 10. The qualitative results of Wonder3D on various animal
objects.
Wonder3D