The radiance fields style transfer is an emerging field that has recently gained popularity as a means of 3D scene stylization, thanks to the outstanding performance of neural radiance fields in 3D reconstruction and view synthesis. We highlight a research gap in radiance fields style transfer, the lack of sufficient perceptual controllability, motivated by the existing concept in the 2D image style transfer. In this paper, we present ARF-Plus, a 3D neural style transfer framework offering manageable control over perceptual factors, to systematically explore the perceptual controllability in 3D scene stylization. Four distinct types of controls - color preservation control, (style pattern) scale control, spatial (selective stylization area) control, and depth enhancement control - are proposed and integrated into this framework. Results from real-world datasets, both quantitative and qualitative, show that the four types of controls in our ARF-Plus framework successfully accomplish their corresponding perceptual controls when stylizing 3D scenes. These techniques work well for individual style inputs as well as for the simultaneous application of multiple styles within a scene. This unlocks a realm of limitless possibilities, allowing customized modifications of stylization effects and flexible merging of the strengths of different styles, ultimately enabling the creation of novel and eye-catching stylistic effects on 3D scenes.

翻译：辐射场风格迁移是一个新兴领域，其得益于神经辐射场在三维重建和视图合成中的卓越性能，作为3D场景风格化手段近期备受关注。我们基于现有二维图像风格迁移中的感知可控性概念，揭示了辐射场风格迁移领域缺乏充分感知可控性的研究空白。本文提出ARF-Plus，一个提供感知因子可管理控制的3D神经风格迁移框架，系统探索3D场景风格化中的感知可控性。该框架集成四种差异化控制类型：色彩保持控制、（风格图案）尺度控制、空间（选择性风格化区域）控制及深度增强控制。基于真实世界数据集的定性与定量结果表明，ARF-Plus框架中的四类控制机制在风格化3D场景时成功实现了对应感知控制。这些技术既能有效处理单一风格输入，也可支持场景内多风格同步应用。这打开了无限可能空间，实现了风格化效果的定制化修改与不同风格优势的灵活融合，最终在3D场景上创造新颖夺目的风格化视觉效果。