From 4345e7ba370113c56afbd7e0eda6a1696146a328 Mon Sep 17 00:00:00 2001 From: Jules Date: Tue, 30 Oct 2018 21:14:59 -0400 Subject: data --- .../FDDB: A Benchmark for Face Detection in Unconstrained Settings.csv | 1 + 1 file changed, 1 insertion(+) create mode 100644 datasets/scholar/entries/FDDB: A Benchmark for Face Detection in Unconstrained Settings.csv (limited to 'datasets/scholar/entries/FDDB: A Benchmark for Face Detection in Unconstrained Settings.csv') diff --git a/datasets/scholar/entries/FDDB: A Benchmark for Face Detection in Unconstrained Settings.csv b/datasets/scholar/entries/FDDB: A Benchmark for Face Detection in Unconstrained Settings.csv new file mode 100644 index 00000000..eeb0adb1 --- /dev/null +++ b/datasets/scholar/entries/FDDB: A Benchmark for Face Detection in Unconstrained Settings.csv @@ -0,0 +1 @@ +Fddb: A benchmark for face detection in unconstrained settings|http://www.cs.umass.edu/~elm/papers/fddb.pdf|2010|525|13|17267836250801810690|http://www.cs.umass.edu/~elm/papers/fddb.pdf|http://scholar.google.com/scholar?cites=17267836250801810690&as_sdt=2005&sciodt=0,5&hl=en|http://scholar.google.com/scholar?cluster=17267836250801810690&hl=en&as_sdt=0,5|None|Despite the maturity of face detection research, it remains difficult to compare different algorithms for face detection. This is partly due to the lack of common evaluation schemes. Also, existing data sets for evaluating face detection algorithms do not capture some aspects of face appearances that are manifested in real-world scenarios. In this work, we address both of these issues. We present a new data set of face images with more faces and more accurate annotations for face regions than in previous data sets. We also propose two … -- cgit v1.2.3-70-g09d2