用视频实现疼痛自动评估，基于全注意力机制框架。
A Full Transformer-based Framework for Automatic Pain Estimation using Videos
- 采用双注意力结构的Transformer模型处理视频数据
- 在BioVid数据集上达到当前最优性能
- 适合医疗辅助诊断与智能健康系统研究者
自动疼痛评估对于设计高效疼痛管理系统至关重要，可提供可靠评估并减轻患者痛苦。本研究提出一种全新的全Transformer框架，包含Transformer in Transformer（TNT）模型以及融合交叉注意力与自注意力块的Transformer。基于BioVid数据库中的视频数据进行实验，结果表明该方法在所有主要疼痛估计任务中均取得领先表现，验证了其有效性、高效性及良好的泛化能力。
原文摘要 · Abstract (English)
The automatic estimation of pain is essential in designing an optimal pain management system offering reliable assessment and reducing the suffering of patients. In this study, we present a novel full transformer-based framework consisting of a Transformer in Transformer (TNT) model and a Transformer leveraging cross-attention and self-attention blocks. Elaborating on videos from the BioVid database, we demonstrate state-of-the-art performances, showing the efficacy, efficiency, and generalization capability across all the primary pain estimation tasks.
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