StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fields

• URL: http://arxiv.org/abs/2303.10598v3
• Date: Fri, 24 Mar 2023 06:57:50 GMT
• Title: StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fields
• Authors: Kunhao Liu, Fangneng Zhan, Yiwen Chen, Jiahui Zhang, Yingchen Yu, Abdulmotaleb El Saddik, Shijian Lu, Eric Xing
• Abstract summary: StyleRF (Style Radiance Fields) is an innovative 3D style transfer technique. It employs an explicit grid of high-level features to represent 3D scenes, with which high-fidelity geometry can be reliably restored via volume rendering. It transforms the grid features according to the reference style which directly leads to high-quality zero-shot style transfer.
• Score: 52.19291190355375
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: 3D style transfer aims to render stylized novel views of a 3D scene with multi-view consistency. However, most existing work suffers from a three-way dilemma over accurate geometry reconstruction, high-quality stylization, and being generalizable to arbitrary new styles. We propose StyleRF (Style Radiance Fields), an innovative 3D style transfer technique that resolves the three-way dilemma by performing style transformation within the feature space of a radiance field. StyleRF employs an explicit grid of high-level features to represent 3D scenes, with which high-fidelity geometry can be reliably restored via volume rendering. In addition, it transforms the grid features according to the reference style which directly leads to high-quality zero-shot style transfer. StyleRF consists of two innovative designs. The first is sampling-invariant content transformation that makes the transformation invariant to the holistic statistics of the sampled 3D points and accordingly ensures multi-view consistency. The second is deferred style transformation of 2D feature maps which is equivalent to the transformation of 3D points but greatly reduces memory footprint without degrading multi-view consistency. Extensive experiments show that StyleRF achieves superior 3D stylization quality with precise geometry reconstruction and it can generalize to various new styles in a zero-shot manner.

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