  Creating artistic 3D scenes can be time-consuming and requires specialized
knowledge. To address this, recent works such as ARF, use a radiance
field-based approach with style constraints to generate 3D scenes that resemble
a style image provided by the user. However, these methods lack fine-grained
control over the resulting scenes. In this paper, we introduce Controllable
Artistic Radiance Fields (CoARF), a novel algorithm for controllable 3D scene
stylization. CoARF enables style transfer for specified objects, compositional
3D style transfer and semantic-aware style transfer. We achieve controllability
using segmentation masks with different label-dependent loss functions. We also
propose a semantic-aware nearest neighbor matching algorithm to improve the
style transfer quality. Our extensive experiments demonstrate that CoARF
provides user-specified controllability of style transfer and superior style
transfer quality with more precise feature matching.
