Multi-task and Multi-level Feature Aggregation for Facial Expression Recognition
This repository holds the PyTorch implementation of MMNet in facial expression recognition (FER) field.
Emotion
Num
0
1619
1
355
2
877
3
5957
4
2460
5
867
6
3204
Emotion
Num
0
3995
1
436
2
4097
3
7215
4
4830
5
3171
6
4965
Weighted Sampling
Race
Gender
Age
Emotion
FER(Avg Confusion Matrix)
N
0.8631
0.8217
0.7428
0.8302
0.7514
N
0.7663
0.5469
0.6281
0.8351
0.7457
Y
0.7663
0.7624
0.6004
0.8090
0.7600
Y
0.8638
0.8096
0.7396
0.8380
0.7710
Weighted Sampling
Color
FA
Emotion Acc
Avg Confusion Matrix
N
RGB
Add
69.13
67.39
Y
RGB
Add
69.18
67.24
Y
Gray
Add
69.95
68.09
Y
Gray
Max
70.08
68.96
Aggregation Mode
FER
Elw Add + Random Sampling
75.71
Elw Avg + Weighted Sampling
76.69
Elw Add + Weighted Sampling
77.10
Elw Max + Weighted Sampling
74.89
Elw Min + Weighted Sampling
75.75
None + Weighted Sampling
75.33
Learning Fashion
Race
Gender
Age
FER(Avg Confusion Matrix)
Individual Learning
86.15
82.56
73.79
73.43
Multi-task Learning
86.38
80.96
73.96
77.10
emotion_branch_w
age_branch_w
race_branch_w
gender_branch_w
Emotion_AVG_CM
1
1
1
1
0.7585
3
1
1
1
0.7710
4
1
1
1
0.7628