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Found 3 papers, 3 papers with code
AttendAffectNet–Emotion Prediction of Movie Viewers Using Multimodal Fusion with Self-Attention
The models that use all visual, audio, and text features simultaneously as their inputs performed better than those using features extracted from each modality separately.
AttendAffectNet: Self-Attention based Networks for Predicting Affective Responses from Movies
In this work, we propose different variants of the self-attention based network for emotion prediction from movies, which we call AttendAffectNet.
Multimodal Deep Models for Predicting Affective Responses Evoked by Movies
Interestingly, we also observe that the optical flow is more informative than the RGB in videos, and overall, models using audio features are more accurate than those based on video features when making the final prediction of evoked emotions.
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