In this study, we investigated a deep-learning method for visualizing Cutibacterium acnes (C. acnes) in facial photographs taken with visible-light irradiation. We used a dermatological device to capture photos with UV-light irradiation wherein C. acnes on the faces of people and paired these photos with visible-light images to train a deep learning model. Then, two methods were devised to increase the learning efficiency, namely a method to crop and reduce the size of the image used for learning and a method for highlighting the points where the C. acnes emitted light. These results suggested the potential application of these methods in visualizing C. acnes using only smartphones.