The ability of the brain to integrate multimodal informa- tion is crucial for providing a coherent perceptual expe- rience, with perception being modulated ...

We present experimental results processing facial and body motion cues, showing that our model for emotion-driven attention improves the accuracy of emotion ...

Mar 29, 2023 · A Deep Neural Model for Emotion-Driven Multimodal Attention. March 29, 2023. Authors. German Ignacio Parisi. Pablo Barros. Haiyan Wu. Guochun ...

Mar 1, 2024 · This paper makes the first effort in comprehensively summarize recent advances in deep learning-based multimodal emotion recognition (DL-MER) involved in audio ...

Oct 12, 2023 · Multimodal emotion recognition (MER) refers to the identification and understanding of human emotional states by combining different signals ...

In this paper, a Bimodal-LSTM model is introduced to take temporal information into account for emotion recognition with multimodal signals.

We propose a deep learning-based multimodal emotion recognition (MER) called Deep-Emotion, which can adaptively integrate the most discriminating features from ...

Eccentricity Dependent Deep Neural Networks: Modeling Invariance in Human Vision ... A Deep Neural Model for Emotion-Driven Multimodal Attention. March 29, 2023.

In this paper, we propose a three-dimensional convolutional recurrent neural network model (referred to as 3FACRNN network) based on multimodal fusion and ...

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