Research Article
A Deep Multimodal Model for Predicting Affective Responses Evoked by Movies Based on Shot Segmentation
Table 3
Comparison of state-of-the-art results for intended emotion prediction.
| Models | Arousal | Valence | MSE | PCC | MSE | PCC |
| Malandrakis et al. [4] | 0.17 | 0.54 | 0.24 | 0.23 | Goyal et al. [6] | — | 0.62 ± 0.16 | — | 0.29 ± 0.16 | Sivaprasad et al. [7] | 0.08 ± 0.04 | 0.84 ± 0.06 | 0.21 ± 0.06 | 0.50 ± 0.14 | Thao et al. [9] | 0.13 | 0.62 | 0.19 | 0.25 | Thao et al. [10] | 0.124 | 0.630 | 0.178 | 0.572 |
| Ours (loss1) | 0.1022 | 0.6748 | 0.1654 | 0.3167 | Ours (loss2) | 0.1141 | 0.6582 | 0.1704 | 0.4025 |
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