<![CDATA[The perception of beauty whether applied to a face or any similar subject, differs among people, with assorted values doled out to magnificence levels or positions. Facial beauty assessment has gained significant interest in various domains, including cosmetics, image processing, and artificial intelligence. This review digs into facial beauty prediction utilizing the Attribute Aware Convolutional Neural Network (AACNN) according to the SCUT-FBP5500 benchmark dataset. The study in this paper closes by accentuating the requirement for more comprehensive and adjusted datasets and proposes future exploration bearings to improve model decency and address moral ramifications.]]>
