Video-Mined Task Graphs for Keystep Recognition in Instructional Videos

作者：Kumar Ashutosh, Santhosh Kumar Ramakrishnan, Triantafyllos Afouras, Kristen Grauman · 发表于：arXiv (Cornell University) · 年份：2023 · DOI：10.48550/arxiv.2307.08763 · 被引用次数：10 · 研究领域：Human Pose and Action Recognition、Hand Gesture Recognition Systems、Context-Aware Activity Recognition Systems

Procedural activity understanding requires perceiving human actions in terms of a broader task, where multiple keysteps are performed in sequence across a long video to reach a final goal state -- such as the steps of a recipe or a DIY fix-it task. Prior work largely treats keystep recognition in isolation of this broader structure, or else rigidly confines keysteps to align with a predefined sequential script. We propose discovering a task graph automatically from how-to videos to represent probabilistically how people tend to execute keysteps, and then leverage this graph to regularize keystep recognition in novel videos. On multiple datasets of real-world instructional videos, we show the impact: more reliable zero-shot keystep localization and improved video representation learning, exceeding the state of the art.