Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression

ICCV 2019 Xinyao WangLiefeng BoLi Fuxin

Heatmap regression with a deep network has become one of the mainstream approaches to localize facial landmarks. However, the loss function for heatmap regression is rarely studied... (read more)

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Evaluation Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK COMPARE
Face Alignment 300W AWing (Inter-ocular Norm) Mean Error Rate private 3.56 # 2
Face Alignment 300W AWing (Inter-ocular Norm) AUC0.08 private 64.40 # 3
Face Alignment 300W AWing (Inter-ocular Norm) Failure private 0.33% # 2
Face Alignment 300W AWing (Inter-ocular Norm) Fullset (public) 3.07 # 1
Face Alignment 300W AWing (Inter-pupil Norm) Mean Error Rate private 3.56 # 2
Face Alignment 300W AWing (Inter-pupil Norm) AUC0.08 private 55.76 # 5
Face Alignment 300W AWing (Inter-pupil Norm) Failure private 0.83% # 3
Face Alignment 300W AWing (Inter-pupil Norm) Fullset (public) 4.31 # 10
Face Alignment COFW AWing Mean Error Rate 4.94 # 1