Beauty lies in the face of the beholder: A Bi-channel CNN architecture for attractiveness modeling in matrimony

Abstract

Profile images play an important role in partner selection in a matrimony or dating site. The hypothesis of this paper is that perceived beauty of a profile image is a subjective opinion based on who is viewing the image. We validate this hypothesis by showing that this subjective bias for attractiveness can be learnt from the sender-receiver image pairs. We train a Bi-channel CNN based deep architecture that incorporates the visual features of both users and learns the attractiveness of sender as perceived by the receiver. This network was trained and tested on 3.5 million image pairs and achieved an accuracy of 69% with images alone, thus proving that rather than the eye, beauty lies in the face of the beholder. When this network was used in conjunction with other profile features such as age, city and caste, it further improved the accuracy of the system by a 5% relative number.