summaryrefslogtreecommitdiff
path: root/datasets/scholar/entries/Robust face landmark estimation under occlusion .csv
diff options
context:
space:
mode:
authorJules Laplace <julescarbon@gmail.com>2018-10-31 02:15:42 +0100
committerJules Laplace <julescarbon@gmail.com>2018-10-31 02:15:42 +0100
commita16c3cf801b70670dffc7041d92f7ccec56a0e18 (patch)
tree189c6f52c347cad780aba982c04efb8668eaa57f /datasets/scholar/entries/Robust face landmark estimation under occlusion .csv
parent640fb390baf494571114bc50b8059c9823ee899e (diff)
parentab81e78a0bca427ba9b0283ec3a1b5fc2d98cf2d (diff)
Merge branch 'master' of asdf.us:megapixels_dev
Diffstat (limited to 'datasets/scholar/entries/Robust face landmark estimation under occlusion .csv')
-rw-r--r--datasets/scholar/entries/Robust face landmark estimation under occlusion .csv1
1 files changed, 1 insertions, 0 deletions
diff --git a/datasets/scholar/entries/Robust face landmark estimation under occlusion .csv b/datasets/scholar/entries/Robust face landmark estimation under occlusion .csv
new file mode 100644
index 00000000..c1245878
--- /dev/null
+++ b/datasets/scholar/entries/Robust face landmark estimation under occlusion .csv
@@ -0,0 +1 @@
+Robust face landmark estimation under occlusion|http://scholar.google.com/https://www.cv-foundation.org/openaccess/content_iccv_2013/html/Burgos-Artizzu_Robust_Face_Landmark_2013_ICCV_paper.html|2013|441|16|6035683787196907858|None|http://scholar.google.com/scholar?cites=6035683787196907858&as_sdt=2005&sciodt=0,5&hl=en|http://scholar.google.com/scholar?cluster=6035683787196907858&hl=en&as_sdt=0,5|None|Human faces captured in real-world conditions present large variations in shape and occlusions due to differences in pose, expression, use of accessories such as sunglasses and hats and interactions with objects (eg food). Current face landmark estimation approaches struggle under such conditions since they fail to provide a principled way of handling outliers. We propose a novel method, called Robust Cascaded Pose Regression (RCPR) which reduces exposure to outliers by detecting occlusions explicitly and using …