Table 2.
Performance Comparison of Representative Methods for Eight-Class Evoked Emotion Classification From Images on the FI Dataset, Measured by Average Accuracy (%). *The Results Are Mainly Obtained From MDAN [234] and SimEmotion [212]
| Method | Venue | Accuracy (%) |
|---|---|---|
|
| ||
| SentiBank [200] | ACM MM 2013 | 44.5 |
| Artistic principles [188] | ACM MM 2014 | 46.1 |
| DeepSentiBank [239] | arXiv 2014 | 53.2 |
| Fine-tuned AlexNet [203] | NeurIPS 2012 | 58.3 |
| Fine-tuned VGG-16 [204] | ICLR 2015 | 65.5 |
| Fine-tuned ResNet-101 [205] | CVPR 2016 | 66.2 |
| Porgressive CNN [215] | AAAI 2015 | 56.2 |
| MldrNet [231] | NPL 2020 | 65.2 |
| WSCNet [227] | CVPR 2018 | 70.1 |
| PDANet [226] | ACM MM 2019 | 72.1 |
| MlrCNN [230] | NEUCOM 2019 | 75.5 |
| SAVEAN [219] | TIP 2021 | 72.4 |
| SOLVER [232] | TIP 2021 | 72.3 |
| MDAN [234] | CVPR 2022 | 76.4 |
| SimEmotion [212] | TAFFC 2022 | 80.3 |