  Systems that analyse faces have seen significant improvements in recent years
and are today used in numerous application scenarios. However, these systems
have been found to be negatively affected by facial alterations such as
tattoos. To better understand and mitigate the effect of facial tattoos in
facial analysis systems, large datasets of images of individuals with and
without tattoos are needed. To this end, we propose a generator for
automatically adding realistic tattoos to facial images. Moreover, we
demonstrate the feasibility of the generation by using a deep learning-based
model for removing tattoos from face images. The experimental results show that
it is possible to remove facial tattoos from real images without degrading the
quality of the image. Additionally, we show that it is possible to improve face
recognition accuracy by using the proposed deep learning-based tattoo removal
before extracting and comparing facial features.
