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Research map / 3D vision / Human pose estimation

Simultaneous Facial Landmark Detection, Pose and Deformation Estimation Under Facial Occlusion

CVPR 2017 · 3D vision › Human pose estimation · approach: Learned camera pose estimation · 79 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
jointly estimate facial landmarks, head pose, deformation, and occlusion instead of estimating landmarks alone (ablation)COFW landmark detection · COFWnormalized landmark error: 7.70 -> 6.40Helped
add occlusion prediction to landmark detection (ablation)cascade regression landmark detector · COFWnormalized landmark error: 7.70 -> 6.61Helped
add head pose and facial deformation information to the occlusion-aware landmark detector (ablation)ours occlusion · COFWnormalized landmark error: 6.61 -> 6.40Helped
use the proposed method for continuous head pose estimationhead pose estimation · BU head tracking databasemean absolute error (average): 4.6 -> 4.4Helped
use the proposed method for yaw estimationhead pose estimation · MultiPIEyaw mean absolute error: 5.31 -> 5.36No clear effect
use the proposed method for facial landmark detectionlandmark detector · MultiPIE near-frontalaverage pixel error: 4.09 -> 3.51Helped
use the proposed method for facial landmark detection across poseslandmark detector · MultiPIE all posesaverage pixel error: 4.39 -> 3.50Helped
use the proposed method for occlusion predictionfacial occlusion predictor · COFWrecall at precision 80%: 37.0% -> 44.43%Helped

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