AutoStruct-Video: LLM-Guided Spatio-Temporal Reasoning for Multi-Event Video Generation
Year: 2026
Type: preprint
Abstract: Generating videos that depict multiple distinct events unfolding coherently over time — for example, a sequence of causally or narratively connected actions — remains challenging for current video generation models, which often struggle to maintain long-range narrative and spatio-temporal consistency across multiple depicted events. This project proposes AutoStruct-Video, a framework that uses a large language model to plan the spatio-temporal structure of a multi-event video (event sequencing, spatial layout, temporal transitions) before guiding a video generation model to synthesize content that adheres to this explicit structural plan, improving coherence across complex, multi-event video generation.
Author: GUPTA, ADISHREE
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7203863220
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