From 640fb390baf494571114bc50b8059c9823ee899e Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Wed, 31 Oct 2018 02:15:35 +0100 Subject: data --- .../entries/Attribute and Simile Classifiers for Face Verification.csv | 2 ++ 1 file changed, 2 insertions(+) create mode 100644 datasets/scholar/entries/Attribute and Simile Classifiers for Face Verification.csv (limited to 'datasets/scholar/entries/Attribute and Simile Classifiers for Face Verification.csv') diff --git a/datasets/scholar/entries/Attribute and Simile Classifiers for Face Verification.csv b/datasets/scholar/entries/Attribute and Simile Classifiers for Face Verification.csv new file mode 100644 index 00000000..1d6e856b --- /dev/null +++ b/datasets/scholar/entries/Attribute and Simile Classifiers for Face Verification.csv @@ -0,0 +1,2 @@ +Attribute and simile classifiers for face verification|http://scholar.google.com/https://ieeexplore.ieee.org/abstract/document/5459250/|2009|1231|22|4063408445858122425|None|http://scholar.google.com/scholar?cites=4063408445858122425&as_sdt=2005&sciodt=0,5&hl=en|http://scholar.google.com/scholar?cluster=4063408445858122425&hl=en&as_sdt=0,5|None|We present two novel methods for face verification. Our first method-“attribute” classifiers-uses binary classifiers trained to recognize the presence or absence of describable aspects of visual appearance (eg, gender, race, and age). Our second method-“simile” classifiers-removes the manual labeling required for attribute classification and instead learns the similarity of faces, or regions of faces, to specific reference people. Neither method requires costly, often brittle, alignment between image pairs; yet, both methods produce compact … +Attribute and simile classifiers for face verification|None|2009|10|0|7848300437118808957|None|http://scholar.google.com/scholar?cites=7848300437118808957&as_sdt=2005&sciodt=0,5&hl=en|None|None|None -- cgit v1.2.3-70-g09d2