学习从观察和叙述中分割动作
Learning to Segment Actions from Observation and Narration
摘要：
我们应用一个生成段模型的任务结构，指导下的叙述，在视频中的动作分割。我们专注于无监督和弱监督的设置，在训练过程中没有动作标签。尽管它的简单性，我们的模型执行竞争力与以前的工作的自然主义教学视频的数据集。我们的模型允许我们改变训练中使用的监督来源，我们发现任务结构和叙述语言都在分割质量方面提供了很大的好处。
英文摘要：
We apply a generative segmental model of task structure, guided by narration, to action segmentation in video. We focus on unsupervised and weakly-supervised settings where no action labels are known during training. Despite its simplicity, our model performs competitively with previous work on a dataset of naturalistic instructional videos. Our model allows us to vary the sources of supervision used in training, and we find that both task structure and narrative language provide large benefits in segmentation quality.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
