In this work, we introduce our method of outdoor scene relighting for Neural Radiance Fields (NeRF) named Sun-aligned Relighting TensoRF (SR-TensoRF). SR-TensoRF offers a lightweight and rapid pipeline aligned with the sun, thereby achieving a simplified workflow that eliminates the need for environment maps. Our sun-alignment strategy is motivated by the insight that shadows, unlike viewpoint-dependent albedo, are determined by light direction. We directly use the sun direction as an input during shadow generation, simplifying the requirements of the inference process significantly. Moreover, SR-TensoRF leverages the training efficiency of TensoRF by incorporating our proposed cubemap concept, resulting in notable acceleration in both training and rendering processes compared to existing methods.

该论文介绍了一种名为SR-TensoRF的神经辐射场（NeRF）的户外场景再照明方法。SR-TensoRF通过与太阳对齐的轻量级和快速流程实现了简化的工作流程，不再需要环境映射。我们基于晴天的见解形成了太阳对齐策略，因为与视点相关的阴影是由光线方向决定的。在阴影生成过程中，我们直接使用太阳方向作为输入，极大地简化了推理过程的要求。此外，SR-TensoRF利用了TensoRF的训练效率，结合了我们提出的立方体贴图概念，相比现有方法在训练和渲染过程中加速明显。

基于TensoRF的快速太阳对准户外场景照明重新调整