Multi-Attention Fusion Artistic Radiance Fields and Beyond

Abstract

We present MRF (multi-attention fusion artistic radiance fields), a novel approach to 3D scene stylisation that synthesises artistic rendering by integrating stylised 2D images with neural radiance fields. Our method effectively incorporates high-frequency stylistic elements from 2D artistic representations while maintaining geometric consistency across multiple viewpoints. To address the challenges of view-dependent stylisation coherence and semantic fidelity, we introduce two key components: (1) a multi-scale attention module (MAM) that facilitates hierarchical feature extraction and fusion across different spatial resolutions and (2) a CLIP-guided semantic consistency module that preserves the underlying scene structure during style transfer. Through extensive experimentation, we demonstrate that MRF achieves superior stylisation quality and detail preservation compared to state-of-the-art methods, particularly in capturing fine artistic details while maintaining view consistency. Our approach represents a significant advancement in neural rendering-based artistic stylisation of 3D scenes.