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+SCUT-FBP: A benchmark dataset for facial beauty perception|http://scholar.google.com/https://arxiv.org/abs/1511.02459|2015|17|4|3066282784180910292|None|http://scholar.google.com/scholar?cites=3066282784180910292&as_sdt=2005&sciodt=0,5&hl=en|http://scholar.google.com/scholar?cluster=3066282784180910292&hl=en&as_sdt=0,5|None|In this paper, a novel face dataset with attractiveness ratings, namely, the SCUT-FBP dataset, is developed for automatic facial beauty perception. This dataset provides a benchmark to evaluate the performance of different methods for facial attractiveness prediction, including the state-of-the-art deep learning method. The SCUT-FBP dataset contains face portraits of 500 Asian female subjects with attractiveness ratings, all of which have been verified in terms of rating distribution, standard deviation, consistency, and self …