all AI news
Freditor: High-Fidelity and Transferable NeRF Editing by Frequency Decomposition
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
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 …
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
MLOps Engineer - Hybrid Intelligence
@ Capgemini | Madrid, M, ES
Analista de Business Intelligence (Industry Insights)
@ NielsenIQ | Cotia, Brazil