From ee3d0d98e19f1d8177d85af1866fd0ee431fe9ea Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Sun, 25 Nov 2018 22:19:15 +0100 Subject: moving stuff --- ...ition in Unconstrained Videos with Matched Background Similarity.csv | 2 ++ 1 file changed, 2 insertions(+) create mode 100644 scraper/datasets/scholar/entries/Face Recognition in Unconstrained Videos with Matched Background Similarity.csv (limited to 'scraper/datasets/scholar/entries/Face Recognition in Unconstrained Videos with Matched Background Similarity.csv') diff --git a/scraper/datasets/scholar/entries/Face Recognition in Unconstrained Videos with Matched Background Similarity.csv b/scraper/datasets/scholar/entries/Face Recognition in Unconstrained Videos with Matched Background Similarity.csv new file mode 100644 index 00000000..2f1e41af --- /dev/null +++ b/scraper/datasets/scholar/entries/Face Recognition in Unconstrained Videos with Matched Background Similarity.csv @@ -0,0 +1,2 @@ +Face recognition in unconstrained videos with matched background similarity|http://scholar.google.com/https://ieeexplore.ieee.org/abstract/document/5995566/|2011|657|10|5401801956686441353|None|http://scholar.google.com/scholar?cites=5401801956686441353&as_sdt=2005&sciodt=0,5&hl=en|http://scholar.google.com/scholar?cluster=5401801956686441353&hl=en&as_sdt=0,5|None|Recognizing faces in unconstrained videos is a task of mounting importance. While obviously related to face recognition in still images, it has its own unique characteristics and algorithmic requirements. Over the years several methods have been suggested for this problem, and a few benchmark data sets have been assembled to facilitate its study. However, there is a sizable gap between the actual application needs and the current state of the art. In this paper we make the following contributions.(a) We present a comprehensive … +Face Recognition in Unconstrained Videos with Matched Background Similarity|http://www.cs.tau.ac.il/thesis/thesis/Maoz.Itay-MSc.Thesis.pdf|2012|0|0|None|http://www.cs.tau.ac.il/thesis/thesis/Maoz.Itay-MSc.Thesis.pdf|None|None|None|Recognizing faces in unconstrained videos is a task of mounting importance. While obviously related to face recognition in still images, it has its own unique characteristics and algorithmic requirements. Over the years several methods have been suggested for this problem, and a few benchmark data sets have been assembled to facilitate its study. However, there is a sizable gap between the actual application needs and the current state of the art. In this work we make the following contributions:(a) We present a comprehensive … -- cgit v1.2.3-70-g09d2