集成技术2025，Vol.14Issue(1)：9-24,16.DOI:10.12146/j.issn.2095-3135.20241201002
文本引导视频预测大模型的场景动态控制综述
A Review of Scene Dynamic Control in Text-Guided Video Prediction Large Models
摘要
Abstract
In recent years,the rapid development of generative AI has made text-driven video prediction large models a hot topic in academia and industry.Video prediction and generation should address temporal dynamics and consistency,requiring precise control of scene structures,subject behaviors,camera movements,and semantic expressions.One major challenge is accurately controlling scene dynamics in video prediction to achieve high-quality,semantically consistent outputs.Researchers have proposed key control methods,including camera control enhancement,reference video control,semantic consistency enhancement,and subject feature control improvement.These methods aim to improve generation quality,ensuring outputs align with historical context while meeting user needs.This paper systematically explores the core concepts,advantages,limitations,and future directions of these four control approaches.关键词
文本驱动视频预测/动态控制/相机控制/语义增强/主体特征控制Key words
text-driven video prediction/dynamic control/camera control/semantic enhancement/subject feature control分类
信息技术与安全科学引用本文复制引用
吴福祥,程俊..文本引导视频预测大模型的场景动态控制综述[J].集成技术,2025,14(1):9-24,16.基金项目
国家自然科学基金项目(U21A20487,62372440) This work is supported by National Natural Science Foundation of China(U21A20487,62372440) （U21A20487,62372440）
