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authoradamhrv <adam@ahprojects.com>2018-12-15 19:57:49 +0100
committeradamhrv <adam@ahprojects.com>2018-12-15 19:57:49 +0100
commit82b2c0b5d6d7baccbe4d574d96e18fe2078047d7 (patch)
treea8784b7ec2bc5a0451c252f66a6b786f3a2504f5 /scraper/datasets/scholar/entries/Face detection, pose estimation and landmark localization in the wild.csv
parent8e978af21c2b29f678a09701afb3ec7d65d0a6ab (diff)
parentc5b02ffab8d388e8a2925e51736b902a48a95e71 (diff)
Merge branch 'master' of github.com:adamhrv/megapixels_dev
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+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 …