论文标题
学习从观察和叙述中分割动作
Learning to Segment Actions from Observation and Narration
论文作者
论文摘要
我们将任务结构的生成分段模型应用于叙事的指导，并在视频中进行的动作细分。我们专注于无监督和弱监督的环境，在训练过程中未知动作标签。尽管它很简单，但我们的模型还是在自然主义教学视频数据集上的先前工作中竞争性的。我们的模型使我们能够改变培训中使用的监督源，我们发现任务结构和叙事语言都为细分质量带来了巨大的好处。
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.
