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From Short Clips to Real-Time Streams: Identity-Aware Supervision and Context-Efficient Generation for Video Face Swapping

Zekai Luo, Yuwei Liang, Ruiqi Ma, Haoyu Huang, Xuehao Wang, Huanyi Zheng, Mingyu Liu, Linhao Zhong · 2026 · arXiv

DOI: 10.48550/arXiv.2610.26681 · open-access PDF

Japanese

ビデオ顔交換は、その他の属性と動きを維持しながら、ターゲットビデオに参照アイデンティティを転送します。参照ガイドフローベースの方法における最近の進歩にもかかわらず、信頼性の高いアイデンティティ転送、高信頼性、長いビデオストリームでのリアルタイム生成を共同で達成することは依然として課題です。この課題に対処するために、我々は、参照ガイドフローのビデオ顔交換のタスク特有の構造を再考します。第一に、顔交換は、ほとんどの視覚コンテンツを保存しながら、アイデンティを変更するだけですが、フローマッチング監督はこれらの変化に弱く敏感です。

Machine translation (Meta M2M100); the English original follows.

Abstract

Video face swapping transfers the reference identity to a target video while preserving its other attributes and motion. Despite recent progress in reference-guided flow-based methods, jointly achieving faithful identity transfer, high fidelity, and real-time generation over long video streams remains challenging. To address this challenge, we rethink the task-specific structure of reference-guided video face swapping. First, face swapping changes only identity while preserving most visual content, yet flow-matching supervision is weakly sensitive to these changes. We therefore develop Joint R

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