Sep 25, 2020 · Representation and fusion of features are the most crucial tasks in multimodal emotion recognition research. Self Supervised Learning (SSL) has ...
This work introduces a novel Transformers and Attention-based fusion mechanism that can combine multimodal SSL features and achieve state-of-the-art results.
Dec 9, 2024 · Representation and fusion of features are the most crucial tasks in multimodal emotion recognition research. Self Supervised Learning (SSL) has ...
The code for our IEEE ACCESS (2020) paper Multimodal Emotion Recognition with Transformer-Based Self Supervised Feature Fusion.
Representation and fusion of features are the most crucial tasks in multimodal emotion recognition research. Self Supervised Learning (SSL) has become a ...
Mar 29, 2023 · We propose a novel self-supervised learning (SSL) framework for wearable emotion recognition, where efficient multimodal fusion is realized.
Sep 9, 2024 · To address the above issues, we propose a novel self-supervised learning (SSL) framework for wearable emotion recognition, where efficient ...
People also ask
What is multimodal emotion recognition?
What is multimodal feature fusion?
We propose a novel self-supervised learning (SSL) framework for wearable emotion recognition, where efficient multimodal fusion is realized.
Our results indicate that multimodal textualization provides lower accuracy than feature-based models on C-EXPR-DB, where text transcripts are captured in the ...
In this paper, we present a Modality-Agnostic Transformer based Self-Supervised Learning (MATS 2 L) for emotion recognition using physiological signals.