CoARF: Controllable 3D Artistic Style Transfer for Radiance Fields
<|reference_start|>CoARF: Controllable 3D Artistic Style Transfer for Radiance Fields: 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.<|reference_end|>
@article{zhang2024coarf:,
    title={CoARF: Controllable 3D Artistic Style Transfer for Radiance Fields},
    author={Deheng Zhang, Clara Fernandez-Labrador, Christopher Schroers},
    journal={arXiv preprint arXiv:2404.14967},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.14967},
    primaryClass={cs.CV cs.AI cs.GR}
}