arXiv AI By Kim Sung-Bin, Joohyun Chang, David Harwath, Tae-Hyun Oh

FacEDiT: Talking Head Video Editing via Facial Motion Infilling

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FacEDiT is a mask‑controlled model for editing local segments of talking head videos by infilling facial motion from speech and surrounding context. It uses a self‑supervised pretext task that masks a motion span during training, enabling variable‑duration local rewriting while preserving identity, unedited regions, and boundary continuity. The authors also release FacEDiTBench, a benchmark covering diverse edit types and lengths, and demonstrate that FacEDiT achieves accurate, speech‑aligned edits with strong identity preservation and seamless transitions.

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