  Simulating the effects of skincare products on face is a potential new way to
communicate the efficacy of skincare products in skin diagnostics and product
recommendations. Furthermore, such simulations enable one to anticipate his/her
skin conditions and better manage skin health. However, there is a lack of
effective simulations today. In this paper, we propose the first simulation
model to reveal facial pore changes after using skincare products. Our
simulation pipeline consists of 2 steps: training data establishment and facial
pore simulation. To establish training data, we collect face images with
various pore quality indexes from short-term (8-weeks) clinical studies. People
often experience significant skin fluctuations (due to natural rhythms,
external stressors, etc.,), which introduces large perturbations in clinical
data. To address this problem, we propose a sliding window mechanism to clean
data and select representative index(es) to represent facial pore changes.
Facial pore simulation stage consists of 3 modules: UNet-based segmentation
module to localize facial pores; regression module to predict time-dependent
warping hyperparameters; and deformation module, taking warping hyperparameters
and pore segmentation labels as inputs, to precisely deform pores accordingly.
The proposed simulation is able to render realistic facial pore changes. And
this work will pave the way for future research in facial skin simulation and
skincare product developments.
