Sense Beyond Expressions: Cuteness
This addresses the curiosity about factors influencing cuteness in internet culture, but it is incremental as it applies existing machine learning techniques to a new, niche domain.
The paper tackles the problem of predicting cuteness from personal images by constructing a dataset with annotated cuteness scores and facial attributes, and finds critical attributes and develops a C-LSVM method for prediction, with extensive evaluations validating its effectiveness.
With the development of Internet culture, cuteness has become a popular concept. Many people are curious about what factors making a person look cute. However, there is rare research to answer this interesting question. In this work, we construct a dataset of personal images with comprehensively annotated cuteness scores and facial attributes to investigate this high-level concept in depth. Based on this dataset, through an automatic attributes mining process, we find several critical attributes determining the cuteness of a person. We also develop a novel Continuous Latent Support Vector Machine (C-LSVM) method to predict the cuteness score of one person given only his image. Extensive evaluations validate the effectiveness of the proposed method for cuteness prediction.