论文标题
EventFormer：面部动作单元事件事件检测的AU事件变压器
EventFormer: AU Event Transformer for Facial Action Unit Event Detection
论文作者
论文摘要
面部动作单位（AUS）在人类情感分析中起着必不可少的作用。我们观察到，尽管现实世界应用迫切需要基于AU的高级情绪分析，但先前作品提供的帧级AU结果不能直接用于此类分析。此外，由于AUS是动态过程，因此全球时间信息的利用很重要，但在文献中被严重忽略。为此，我们为AU事件检测提出了事件形式，这是通过将AU事件检测视为多个类特异性集的预测问题来直接从视频序列检测AU事件的第一项工作。在常用的AU基准数据集BP4D上进行的广泛实验显示了在合适的指标下事件形式的优越性。
Facial action units (AUs) play an indispensable role in human emotion analysis. We observe that although AU-based high-level emotion analysis is urgently needed by real-world applications, frame-level AU results provided by previous works cannot be directly used for such analysis. Moreover, as AUs are dynamic processes, the utilization of global temporal information is important but has been gravely ignored in the literature. To this end, we propose EventFormer for AU event detection, which is the first work directly detecting AU events from a video sequence by viewing AU event detection as a multiple class-specific sets prediction problem. Extensive experiments conducted on a commonly used AU benchmark dataset, BP4D, show the superiority of EventFormer under suitable metrics.
