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Leveraging Deepfakes to Close the Domain Gap between Real and Synthetic Images in Facial Capture Pipelines
[article]
2022
arXiv
pre-print
We propose an end-to-end pipeline for both building and tracking 3D facial models from personalized in-the-wild (cellphone, webcam, youtube clips, etc.) video data. First, we present a method for automatic data curation and retrieval based on a hierarchical clustering framework typical of collision detection algorithms in traditional computer graphics pipelines. Subsequently, we utilize synthetic turntables and leverage deepfake technology in order to build a synthetic multi-view stereo
arXiv:2204.10746v2
fatcat:4xdsb657pzaavk6tixma7jhrau