From ee3d0d98e19f1d8177d85af1866fd0ee431fe9ea Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Sun, 25 Nov 2018 22:19:15 +0100 Subject: moving stuff --- .../SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception.csv | 1 + 1 file changed, 1 insertion(+) create mode 100644 scraper/datasets/scholar/entries/SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception.csv (limited to 'scraper/datasets/scholar/entries/SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception.csv') diff --git a/scraper/datasets/scholar/entries/SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception.csv b/scraper/datasets/scholar/entries/SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception.csv new file mode 100644 index 00000000..9215c287 --- /dev/null +++ b/scraper/datasets/scholar/entries/SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception.csv @@ -0,0 +1 @@ +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 … -- cgit v1.2.3-70-g09d2