April 4, 2024, 4:45 a.m. | Yisheng He, Weihao Yuan, Siyu Zhu, Zilong Dong, Liefeng Bo, Qixing Huang

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.02514v1 Announce Type: new
Abstract: This paper enables high-fidelity, transferable NeRF editing by frequency decomposition. Recent NeRF editing pipelines lift 2D stylization results to 3D scenes while suffering from blurry results, and fail to capture detailed structures caused by the inconsistency between 2D editings. Our critical insight is that low-frequency components of images are more multiview-consistent after editing compared with their high-frequency parts. Moreover, the appearance style is mainly exhibited on the low-frequency components, and the content details especially reside …

arxiv cs.cv editing fidelity nerf type

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