Neural Impostor：通过显式形状操控编辑神经辐射场
Neural Impostor: Editing Neural Radiance Fields with Explicit Shape Manipulation
AI总结：
针对神经辐射场几何编辑难度大的问题，提出结合显式四面体网格与多网格隐式场的Neural Impostor混合表示及完整编辑流程，可在保留复杂外观的同时实现变形、合成等操作，在3D内容创作领域具有变革潜力。
摘要：
神经辐射场（Neural Radiance Fields, NeRF）极大推动了高真实感、高表现力3D场景的生成。然而，NeRF的编辑任务，尤其是几何修改方面，仍面临巨大挑战，这一问题阻碍了NeRF在各类应用中的更广泛推广。为解决神经隐式场的高效编辑难题，我们提出Neural Impostor——一种混合表示方法，将显式四面体网格与为显式网格内每个四面体分配的多网格隐式场相结合。我们的框架利用多网格重心坐标编码，在显式形状操控与隐式场几何编辑之间搭建起桥梁，为在保留复杂体素外观的前提下对神经隐式场进行变形、合成与生成提供了务实的解决方案。此外，我们基于一组显式几何编辑操作，提出了一套完整的神经隐式场编辑流程。我们通过包含合成物体编辑与真实采集数据编辑在内的多样示例与实验，验证了系统的鲁棒性与适应性。最后，我们展示了利用多种编辑操作创作合成-采集混合物体的过程，凸显了Neural Impostor在3D内容创建与操控领域的变革性潜力。
英文摘要：
Neural Radiance Fields (NeRF) have significantly advanced the generation of highly realistic and expressive 3D scenes. However, the task of editing NeRF, particularly in terms of geometry modification, poses a significant challenge. This issue has obstructed NeRF's wider adoption across various applications. To tackle the problem of efficiently editing neural implicit fields, we introduce Neural Impostor, a hybrid representation incorporating an explicit tetrahedral mesh alongside a multigrid implicit field designated for each tetrahedron within the explicit mesh. Our framework bridges the explicit shape manipulation and the geometric editing of implicit fields by utilizing multigrid barycentric coordinate encoding, thus offering a pragmatic solution to deform, composite, and generate neural implicit fields while maintaining a complex volumetric appearance. Furthermore, we propose a comprehensive pipeline for editing neural implicit fields based on a set of explicit geometric editing operations. We show the robustness and adaptability of our system through diverse examples and experiments, including the editing of both synthetic objects and real captured data. Finally, we demonstrate the authoring process of a hybrid synthetic-captured object utilizing a variety of editing operations, underlining the transformative potential of Neural Impostor in the field of 3D content creation and manipulation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
