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Mitigating the Impact of Attribute Editing on Face Recognition
March 14, 2024, 4:45 a.m. | Sudipta Banerjee, Sai Pranaswi Mullangi, Shruti Wagle, Chinmay Hegde, Nasir Memon
cs.CV updates on arXiv.org arxiv.org
Abstract: Facial attribute editing using generative models can impair automated face recognition. This degradation persists even with recent identity-preserving models such as InstantID. To mitigate this issue, we propose two techniques that perform local and global attribute editing. Local editing operates on the finer details via a regularization-free method based on ControlNet conditioned on depth maps and auxiliary semantic segmentation masks. Global editing operates on coarser details via a regularization-based method guided by custom loss and …
abstract arxiv automated cs.cv editing face face recognition generative generative models global identity impact instantid issue recognition type via
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