We perform quantitative evaluations of our method’s
ability to preserve the subject’s identity, by comparing the
distribution of identity scores between the input image and
rendered reconstruction, on the LFW dataset [32], against
prior work [24, 25, 26, 67]. Following the existing bench-
mark [25], we evaluate our results using VGG-Face [53].
We present our analysis in Fig. 7, measuring the distance

Figure 7.
Quantitative evaluation of similarity scores on
LFW [32], compared with prior work ([26, 67, 24, 25]), using
VGG-Face [53]. We show the cosine similarity distribution be-
tween ground truth and reconstruction.

Figure 8. Reconstructions from images with different illumination
(Digital Emily Project [2]) by our method as well as [18, 42]. We
show the diffuse and specular albedo for all methods (where avail-
able), plus the recovered texture for our method.

4.5. Reﬂectance Prediction
Relightify-Relightable3DFacesfromaSingleImageviaDiffusionModels