论文标题
通过身体，上下文和视觉语义嵌入损失在视频中的情感理解
Emotion Understanding in Videos Through Body, Context, and Visual-Semantic Embedding Loss
论文作者
论文摘要
我们将获胜的意见提交给第一个关于身体表达的情感理解（BEEU）挑战的国际研讨会。基于有关上下文/环境对情感影响的最新文献，以及具有语义含义的视觉表示，我们扩展了时间段网络的框架以适应这些框架。我们的方法在验证集的验证集（BOLD）的验证集（BOLD）上得到了验证，并在测试集中获得了0.26235的情感识别评分，超过了先前的0.2530最佳结果。
We present our winning submission to the First International Workshop on Bodily Expressed Emotion Understanding (BEEU) challenge. Based on recent literature on the effect of context/environment on emotion, as well as visual representations with semantic meaning using word embeddings, we extend the framework of Temporal Segment Network to accommodate these. Our method is verified on the validation set of the Body Language Dataset (BoLD) and achieves 0.26235 Emotion Recognition Score on the test set, surpassing the previous best result of 0.2530.
