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Emotion Recognition In Context On Bold
Métriques
AUC
Average mAP
Résultats
Résultats de performance de divers modèles sur ce benchmark
| Paper Title | |||
|---|---|---|---|
| A. Xenos et al | 69.83 | 26.66 | VLLMs Provide Better Context for Emotion Understanding Through Common Sense Reasoning |
| EmotionCLIP(linear-probe evaluation) | 69.30 | 22.51 | Learning Emotion Representations from Verbal and Nonverbal Communication |
| Pikoulis et al | 66.82 | 19.29 | Leveraging Semantic Scene Characteristics and Multi-Stream Convolutional Architectures in a Contextual Approach for Video-Based Visual Emotion Recognition in the Wild |
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