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 and a teacher-student training strategy 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，为了处理诸如重建场景的后处理与3D内容生成等任务，迫切需要一种能够与隐式3D模型进行交互的编辑方法。先前的研究虽然已从多个角度探索了NeRF编辑，但在编辑灵活性、质量和速度上仍存在局限，无法提供直接的编辑反馈与即时预览。关键挑战在于设计一种局部可编辑的神经表示，使其能直接反映编辑指令并即时更新。为填补这一空白，我们提出了一种针对隐式表示的新型交互式编辑方法与系统，名为Seal-3D，它允许用户以像素级自由方式编辑NeRF模型，并支持多种类NeRF骨干网络，同时实现编辑效果的即时预览。为实现此效果，我们通过提出的代理函数（将编辑指令映射至NeRF模型的原始空间）以及基于局部预训练与全局微调的师生训练策略，解决了相关挑战。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。