High-Precision and Lightweight Facial Landmark Detection Algorithm

Method	Common	Challenging	Full
RCPR	6.18	17.26	8.35
DSRN	4.12	9.68	5.21
DVLN	3.79	7.15	4.45
PCD-CNN	3.67	7.62	4.44
CPM	3.39	8.14	4.36
SAN	3.34	6.60	3.98
LAB	2.98	5.19	3.49
Teacher(our)	3.03	5.26	3.51
Student(our)	3.35	5.78	3.79
Student+KD (our)	3.21	5.41	3.60

Table 2. NME of different algorithms in WFLW dataset unit:%

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Table 2. NME of different algorithms in WFLW dataset unit:%

Method	Test	Pose	Expression	Illumination	Make-up	Occlusion	Blur
CFSS	9.07	21.36	10.09	8.30	8.74	11.76	9.96
DVLN	6.08	11.54	6.78	5.73	5.98	7.33	6.88
MANet	5.41	10.03	5.56	5.54	6.03	7.00	6.25
LAB	5.27	10.24	5.51	5.23	5.15	6.79	6.32
Teacher(our)	5.20	9.01	5.36	5.27	5.45	6.37	6.22
Student(our)	6.04	11.52	6.76	5.70	5.94	7.30	6.87
Student+KD (our)	5.50	9.83	5.89	5.40	5.48	6.88	6.81

Table 3. Network structure, parameter amount and speed of different algorithms
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Table 3. Network structure, parameter amount and speed of different algorithms
Method Backbone Params /M FPS/frame
LAB Houglass 25.1 6
Teacher(our) ResNet50 25 126
Student+KD (our) Light-ResNet50 2.8 162

Table 4. Accuracy of different loss functions on 300W dataset unit:%
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Table 4. Accuracy of different loss functions on 300W dataset unit:%
Method NME
Student 3.79
Student+Pixel 3.67
Student+Pair 3.62
Student+Pixel+Pair 3.60

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Xu Lihuai, Li Zhe, Jiang Jiajia, Duan Fajie, Fu Xiao. High-Precision and Lightweight Facial Landmark Detection Algorithm[J]. Laser & Optoelectronics Progress, 2020, 57(21): 210703

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