From ee3d0d98e19f1d8177d85af1866fd0ee431fe9ea Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Sun, 25 Nov 2018 22:19:15 +0100 Subject: moving stuff --- ... detection, pose estimation and landmark localization in the wild.csv | 1 + 1 file changed, 1 insertion(+) create mode 100644 scraper/datasets/scholar/entries/Face detection, pose estimation and landmark localization in the wild.csv (limited to 'scraper/datasets/scholar/entries/Face detection, pose estimation and landmark localization in the wild.csv') diff --git a/scraper/datasets/scholar/entries/Face detection, pose estimation and landmark localization in the wild.csv b/scraper/datasets/scholar/entries/Face detection, pose estimation and landmark localization in the wild.csv new file mode 100644 index 00000000..43da8a92 --- /dev/null +++ b/scraper/datasets/scholar/entries/Face detection, pose estimation and landmark localization in the wild.csv @@ -0,0 +1 @@ +Face detection, pose estimation, and landmark localization in the wild|http://scholar.google.com/https://ieeexplore.ieee.org/abstract/document/6248014/|2012|1693|7|4876235110904982186|None|http://scholar.google.com/scholar?cites=4876235110904982186&as_sdt=2005&sciodt=0,5&hl=en|http://scholar.google.com/scholar?cluster=4876235110904982186&hl=en&as_sdt=0,5|None|We present a unified model for face detection, pose estimation, and landmark estimation in real-world, cluttered images. Our model is based on a mixtures of trees with a shared pool of parts; we model every facial landmark as a part and use global mixtures to capture topological changes due to viewpoint. We show that tree-structured models are surprisingly effective at capturing global elastic deformation, while being easy to optimize unlike dense graph structures. We present extensive results on standard face benchmarks, as well as a … -- cgit v1.2.3-70-g09d2