  In portraits, eyeglasses may occlude facial regions and generate cast shadows
on faces, which degrades the performance of many techniques like face
verification and expression recognition. Portrait eyeglasses removal is
critical in handling these problems. However, completely removing the
eyeglasses is challenging because the lighting effects (e.g., cast shadows)
caused by them are often complex. In this paper, we propose a novel framework
to remove eyeglasses as well as their cast shadows from face images. The method
works in a detect-then-remove manner, in which eyeglasses and cast shadows are
both detected and then removed from images. Due to the lack of paired data for
supervised training, we present a new synthetic portrait dataset with both
intermediate and final supervisions for both the detection and removal tasks.
Furthermore, we apply a cross-domain technique to fill the gap between the
synthetic and real data. To the best of our knowledge, the proposed technique
is the first to remove eyeglasses and their cast shadows simultaneously. The
code and synthetic dataset are available at
https://github.com/StoryMY/take-off-eyeglasses.
