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AFLW (Annotated Facial Landmarks in the Wild)

Introduced by Martin Köstinger et al. in Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

The Annotated Facial Landmarks in the Wild (AFLW) is a large-scale collection of annotated face images gathered from Flickr, exhibiting a large variety in appearance (e.g., pose, expression, ethnicity, age, gender) as well as general imaging and environmental conditions. In total about 25K faces are annotated with up to 21 landmarks per image.

Source: Nose, Eyes and Ears: Head Pose Estimation by Locating Facial Keypoints

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Benchmarks

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Task	Dataset Variant	Best Model
Head Pose Estimation	AFLW	MNN
Facial Landmark Detection	AFLW-Full	FiFA
Unsupervised Facial Landmark Detection	AFLW (Zhang CVPR 2018 crops)	Conditional Image Generation
Face Alignment	AFLW	SynergyNet
Unsupervised Facial Landmark Detection	AFLW-MTFL	DVE
Facial Landmark Detection	AFLW-Front	FiFA
Face Alignment	AFLW-LFPA	FPN
Face Alignment	AFLW-Full	Binary Face Alignment
Face Alignment	AFLW-PIFA (34 points)	Face alignment
Low-Light Image Enhancement	AFLW (Zhang CVPR 2018 crops)	enligh
Face Alignment	AFLW-PIFA (21 points)	Face alignment