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This is the experimental result of the facial expression recognition of the proposed model using masked face images. In order to show that our proposed model SCN-SAM can effectively suppress the uncertainty of facial expressions caused by masks, we choose ResNet-18 as the baseline and the backbone of SCN-SAM and compare it to SCN. As shown in Figure 11, the SCN-SAM outperforms the baseline and SCN consistently. In the evaluation performed on the masked RAF-DB dataset, SCN does not suppress the uncertainty caused by the presence of masks well, and the performance is almost the same as the baseline model. However, our improved model, SCN-SAM, can suppress the influence of uncertainty caused by masks. The accuracy of the masked RAF-DB is 0.53% higher than that of SCN. The experimental results on the masked FERPlus are even more apparent. In the masked FERPlus, the SCN shows a negative performance, slightly worse than the accuracy of the baseline model. With the help of our proposed SAM module, the accuracy of SCN-SAM is improved by 2.28%. |
IEEE/ICACT20230035 Slide.16
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