Text-based Editing of Talking-head Video ACM Transactions on Graphics 2019 (TOG)
Abstract: We propose a novel method to edit talking-head video based on its transcript to produce a realistic output video in which the dialogue of the speaker has been modified, while maintaining a seamless audio-visual flow (i.e. no jump cuts). Our method automatically annotates an input talking-head video with phonemes, visemes, 3D face pose and geometry, reflectance, expression and scene illumination per frame. To edit a video, the user has to only edit the transcript, and an optimization strategy then chooses segments of the input corpus as base material. The annotated parameters corresponding to the selected segments are seamlessly stitched together and used to produce an intermediate video representation in which the lower half of the face is rendered with a parametric face model. Finally, a recurrent video generation network transforms this representation to a photorealistic video that matches the edited transcript. We demonstrate a large variety of edits, such as the addition, removal, and alteration of words, as well as convincing language translation and full sentence synthesis. Downloads:
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Important Information: Ethical Considerations: Our text-based editing approach lays the foundation for better editing tools for movie post production. Filmed dialogue scenes often require re-timing or editing based on small script changes, which currently requires tedious manual work. Our editing technique also enables easy adaptation of audio-visual video content to specific target audiences: e.g., instruction videos can be fine-tuned to audiences of different backgrounds, or a storyteller video can be adapted to children of different age groups purely based on textual script edits. In short, our work was developed for storytelling purposes. |