With the popularity of implicit neural representations, or neural radiance fields (NeRF), there is a pressing need for editing methods to interact with the implicit 3D models for tasks like post-processing reconstructed scenes and 3D content creation. While previous works have explored NeRF editing from various perspectives, they are restricted in editing flexibility, quality, and speed, failing to offer direct editing response and instant preview. The key challenge is to conceive a locally editable neural representation that can directly reflect the editing instructions and update instantly. To bridge the gap, we propose a new interactive editing method and system for implicit representations, called Seal-3D, which allows users to edit NeRF models in a pixel-level and free manner with a wide range of NeRF-like backbone and preview the editing effects instantly. To achieve the effects, the challenges are addressed by our proposed proxy function mapping the editing instructions to the original space of NeRF models in the teacher model and a two-stage training strategy for the student model with local pretraining and global finetuning. A NeRF editing system is built to showcase various editing types. Our system can achieve compelling editing effects with an interactive speed of about 1 second.

翻译：随着隐式神经表示（即神经辐射场，NeRF）的普及，亟需编辑方法来与隐式三维模型交互，以完成诸如重建场景后处理及三维内容创建等任务。尽管先前的工作已从不同角度探索了NeRF编辑，但它们在编辑灵活性、质量与速度方面存在限制，未能提供直接的编辑响应与即时预览。其关键挑战在于构想一种可局部编辑的神经表示，既能直接反映编辑指令，又能实现即时更新。为弥合这一差距，我们提出了一种新的针对隐式表示的交互式编辑方法与系统，称为Seal-3D，允许用户以像素级且自由的方式编辑NeRF模型（支持多种类NeRF骨干网络），并即时预览编辑效果。为实现这些效果，我们通过所提出的代理函数（将编辑指令映射至教师模型中NeRF模型的原始空间）以及一种包含局部预训练与全局微调的两阶段训练策略（用于学生模型）来应对上述挑战。我们构建了一个NeRF编辑系统以展示多种编辑类型。该系统能以约1秒的交互速度实现令人满意的编辑效果。