Revisiting Domain Adaptation in Video, within and Beyond Recognition

这项研究的目的是确定视频数据的固有性质在处理自我中心计算机视觉中的无监督领域适应设置方面的潜在用例。这项工作将研究不同的方法来捕获额外的视频信息(包括时间知识、多模式知识和冗余信息)并将其整合到现有的机器学习范例中，以及它在弥合在以自我为中心的视频数据集中常见的域转移方面的性能。

The intended purpose of this research is to determine the potential use cases of video data's inherent nature for tackling unsupervised domain adaptation settings in egocentric computer vision. The work will investigate different methods for capturing and integrating additional video information (including temporal knowledge, multi-modal knowledge and redundant information) into existing machine learning paradigms as well as its performance in bridging the domain shifts that are commonplace in egocentric, video datasets.