. Author manuscript; available in PMC: 2019 Jun 26.

Published in final edited form as: Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit. 2018 Dec 17;2018:2090–2099. doi: 10.1109/CVPR.2018.00223

Table 3.

Performance comparison on EmotioNet [2] test set. Braces indicate training images with different amount and annotations (see Sec. 4.1 for details). Bracketed and bold numbers indicate the best and second best performance.

AU	F1						S score
AU	AlexNet ${\begin{matrix} g t 15 k \\ wlb 10 k \end{matrix}}$	AlexNet ${\begin{matrix} g t 15 k \\ wsc 10 k \end{matrix}}$	AlexNet ${\begin{matrix} g t 25 k \end{matrix}}$	DRML ${\begin{matrix} g t 25 k \end{matrix}}$	AlexNet ${\begin{matrix} g t 25 k \\ wsc 25 k \end{matrix}}$	DRML ${\begin{matrix} g t 25 k \\ wsc 25 k \end{matrix}}$	AlexNet ${\begin{matrix} g t 15 k \\ wlb 10 k \end{matrix}}$	AlexNet ${\begin{matrix} g t 15 k \\ wsc 10 k \end{matrix}}$	AlexNet ${\begin{matrix} g t 25 k \end{matrix}}$	DRML ${\begin{matrix} g t 25 k \end{matrix}}$	AlexNet ${\begin{matrix} g t 25 k \\ wsc 25 k \end{matrix}}$	DRML ${\begin{matrix} g t 25 k \\ wsc 25 k \end{matrix}}$
1	11.8	19.8	24.2	25.3	25.3	[26.3]	[83.6]	82.6	76.1	76.5	78.2	78.9
4	23.9	32.5	34.7	[35.7]	34.5	35.5	53.9	[63.9]	63.0	61.8	62.9	61.9
5	26.6	37.6	39.5	40.0	39.3	[40.3]	[87.5]	86.4	80.1	79.6	79.2	80.1
6	58.8	73.5	73.1	75.3	75.6	[78.7]	69.4	74.8	77.3	78.5	78.6	[79.6]
12	82.1	87.1	86.8	86.6	87.4	[88.1]	73.9	79.1	79.5	78.1	80.5	[80.8]
25	82.1	84.3	88.5	[88.9]	88.8	[88.9]	61.4	67.2	77.1	78.8	78.6	[78.9]
26	24.3	40.2	45.6	46.2	47.7	[49.1]	[79.1]	68.5	75.7	76.7	77.6	78.2
Avg.	44.2	53.6	56.1	56.9	57.0	[58.1]	72.6	74.6	75.5	75.7	[76.5]	75.9