title: Seal-3D: Interactive Pixel-Level Editing for Neural Radiance Fields
summary: 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.
paper_authors._id: 64c74febaedc4337783d06e0
paper_authors.name: Xiangyu Wang
paper_authors._id: 64c74febaedc4337783d06e1
paper_authors.name: Jingsen Zhu
paper_authors._id: 64c74febaedc4337783d06e2
paper_authors.name: Qi Ye
paper_authors._id: 64c74febaedc4337783d06e3
paper_authors.name: Yuchi Huo
paper_authors._id: 64c74febaedc4337783d06e4
paper_authors.name: Yunlong Ran
paper_authors._id: 64c74febaedc4337783d06e5
paper_authors.name: Zhihua Zhong
paper_authors._id: 64c74febaedc4337783d06e6
paper_authors.name: Jiming Chen
paper_title: Seal-3D: Interactive Pixel-Level Editing for Neural Radiance Fields
paper_summary: 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.
paper_ai_keywords: neural radiance fields (NeRF) implicit representations post-processing 3D content creation NeRF editing cross-attention layers pixel-level editing free editing proxy function teacher-student training strategy local pretraining global finetuning