Video relation detection problem refers to the detection of the relationship
between different objects in videos, such as spatial relationship and action
relationship. In this paper, we present video relation detection with
trajectory-aware multi-modal features to solve this task.
Considering the complexity of doing visual relation detection in videos, we
decompose this task into three sub-tasks: object detection, trajectory proposal
and relation prediction. We use the state-of-the-art object detection method to
ensure the accuracy of object trajectory detection and multi-modal feature
representation to help the prediction of relation between objects. Our method
won the first place on the video relation detection task of Video Relation
Understanding Grand Challenge in ACM Multimedia 2020 with 11.74\% mAP, which
surpasses other methods by a large margin.

本文提出了利用轨迹感知的多模态特征进行视频关系检测，并将此任务分解为物体检测、轨迹提案和关系预测三个子任务，利用最先进的物体检测方法和多模态特征表示来帮助检测物体之间的关系。我们的方法在 ACM Multimedia 2020 的视频关系理解大挑战的视频关系检测任务中获得了第一名的好成绩（11.74％mAP），超过其他方法。