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Extracting structured information from videos is critical for numerousdownstream applications in the industry. In this paper, we define a significanttask of extracting hierarchical key information from visual texts on videos. Tofulfill this task, we decouple it into four subtasks and introduce twoimplementation solutions called PipVKIE and UniVKIE. PipVKIE sequentiallycompletes the four subtasks in continuous stages, while UniVKIE is improved byunifying all the subtasks into one backbone. Both PipVKIE and UniVKIE leveragemultimodal information from vision, text, and coordinates for featurerepresentation. Extensive experiments on one well-defined dataset demonstratethat our solutions can achieve remarkable performance and efficient inferencespeed.

VKIE: The Application of Key Information Extraction on Video Text