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| author | Jules Laplace <julescarbon@gmail.com> | 2018-11-25 22:19:15 +0100 |
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| committer | Jules Laplace <julescarbon@gmail.com> | 2018-11-25 22:19:15 +0100 |
| commit | ee3d0d98e19f1d8177d85af1866fd0ee431fe9ea (patch) | |
| tree | 41372528e78d4328bc2a47bbbabac7e809c58894 /datasets/scholar/entries/SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception.csv | |
| parent | 255b8178af1e25a71fd23703d30c0d1f74911f47 (diff) | |
moving stuff
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| -rw-r--r-- | datasets/scholar/entries/SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception.csv | 1 |
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diff --git a/datasets/scholar/entries/SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception.csv b/datasets/scholar/entries/SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception.csv deleted file mode 100644 index 9215c287..00000000 --- a/datasets/scholar/entries/SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception.csv +++ /dev/null @@ -1 +0,0 @@ -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 … |