Multimodal Emotion Recognition in Conversation on CMU-MOSEI standard (test)
46.82Accuracy (ACC)GraphSmile
Evaluation Results
| Method | Links | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| GraphSmile2024.07 | 46.82 | 0 | 28.79 | 43.5 | 39.19 | 57.3 | 35.95 | 6.25 | 44.93 | |
| MMGCN2024.07 | 45.67 | 0 | 19.51 | 43.75 | 42.45 | 54.64 | 36.13 | 0 | 44.11 | |
| MM-DFNResult Source=Original Paper2024.07 | 45.29 | 0 | 16.98 | 37.94 | 39.64 | 56.58 | 32.51 | 8.51 | 42.98 | |
| COGMENResult Source=Original Paper2024.07 | 43.9 | — | — | — | — | — | — | — | — | |
| M3NetResult Source=Original Paper2024.07 | 43.67 | 0 | 12.5 | 37.26 | 33.29 | 56.1 | 33.94 | 0 | 41.12 | |
| SACL-LSTMResult Source=Original Paper, Multimodal Feature Fusion Strategy=Direct Concatenation2024.07 | 38.6 | 0 | 0 | 0 | 17.87 | 55.28 | 0 | 0 | 25.95 | |
| DialogueCRNResult Source=Original Paper, Multimodal Feature Fusion Strategy=Direct Concatenation2024.07 | 37.88 | 0 | 4.29 | 7.98 | 25.09 | 51.8 | 3.22 | 0 | 26.55 |