A text-driven face video hair editing method based on timing compensation

By adopting a text-driven face video hair editing method based on time-compensation, the problems of temporal continuity, inaccurate text mapping, and facial attribute destruction in existing technologies are solved. This method achieves high-precision hair editing and facial integrity, supports editing of multiple hairstyles and hair colors, and eliminates inter-frame flickering.

CN122420601APending Publication Date: 2026-07-17HENAN NORMAL UNIV

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
HENAN NORMAL UNIV
Filing Date
2026-04-18
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing technologies for text-driven editing of hair in real-life facial videos suffer from issues such as loss of temporal continuity, inaccurate text-visual mapping, easy destruction of facial attributes, and insufficient preservation of identity and background attributes, resulting in poor editing effects.

Method used

A text-driven face video hair editing method based on temporal compensation is adopted. By combining the inverse mapping coding module, CLIP cross-modal coding module, temporal compensation decoupling module, Hair Mapper module and generator module, the method achieves accurate mapping between text semantics and hair features and inter-frame coherence. The method also combines temporal compensation and feature fusion modules to handle occluded areas and avoids erroneous modification of non-hair areas.

Benefits of technology

It achieves high-precision matching between hair editing results and text semantics, improves inter-frame coherence, fully preserves facial and background attributes, has a high degree of automation, supports editing of multiple hairstyles and hair colors, has an error of less than 5% in matching editing results with text semantics, eliminates inter-frame flickering, and significantly improves identity similarity and background integrity.

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Abstract

本发明公开了一种基于时序补偿的文本驱动人脸视频头发编辑方法,涉及视频头发编辑领域,旨在解决现有技术中时间连贯性缺失,帧间闪烁严重、文本 ‑ 视觉映射不精准、编辑伪影频发、非头发特征保留不足的问题,采用的技术方案是,通过CLIP跨模态编码模块将文本需求的高维向量与编辑帧的原始潜在码融合,进而通过Hair Mapper模块生成光头潜在码,通过FS特征融合模块获得最终编辑特征后,由生成器根据光头潜在码和最终编辑特征合成编辑结果,进而对后续帧进行编辑。本发明能够实现文本语义与头发视觉特征的精准匹配,彻底消除了帧间高频率闪烁现象,面部与背景属性得到完整保留,并能有效避免身份失真、遮挡伪影及背景意外修改等问题。
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