
        Continuous emotion regression estimates a viewer's moment-to-moment valence and arousal while watching video. For familiar videos, the authors find that a simple prior based on which video is playing and the time within it is a strong, low-cost baseline. In subject-held-out tests it came within 0.05 MAE of EEG-fNIRS fusion on the internal evaluation and within 0.32 on the external one. Gains from the brain signals were smaller and varied across participants and videos.

Authors: Minghao Kong, Jiurun Chen, Ying Gao, Xiangbin Meng, Rongjie Wang

Paper: https://arxiv.org/abs/2610.03618v1
      

Continuous emotion regression estimates a viewer's moment-to-moment valence and arousal while watching video. For familiar videos, the authors find that a simple prior based on which video is playing and the time within it is a strong, low-cost baseline. 

Continuous emotion regression estimates a viewer's moment-to-moment valence and arousal while watching video. For familiar videos, the authors find that a simple prior based on which video is playing and the time within it is a strong, low-cost baseline. In subject-held-out tests it came within 0.05 MAE of EEG-fNIRS fusion on the internal evaluation and within 0.32 on the external one. Gains from the brain signals were smaller and varied across participants and videos.

Authors: Minghao Kong, Jiurun Chen, Ying Gao, Xiangbin Meng, Rongjie Wang

Paper: https://arxiv.org/abs/2610.03618v1

Low-Cost Video-Time Priors as a Strong Baseline for EEG-fNIRS Emotion Regression on Familiar Videos

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