考虑物体与环境交互的神经隐式场编辑
Neural Implicit Field Editing Considering Object-environment Interaction
AI总结：
本文提出OSI-aware双流神经渲染系统，通过本征分解、深度图引导修复和点匹配阴影渲染，解决神经隐式场编辑中物体与环境交互及外观变化缺失的问题。
摘要：
基于神经隐式场的三维场景编辑方法已获得广泛关注，并在三维编辑任务中取得了优异成果。然而，现有方法往往混淆物体与场景环境之间的交互，导致渲染视图中无法呈现阴影等场景外观变化。本文提出了一种物体与场景环境交互感知（OSI-aware）系统，这是一种新颖的双流神经渲染系统，能够考虑物体与场景环境的交互。为了从混合信息中获取光照条件，该系统通过本征分解方法成功分离了物体与场景环境之间的交互。为了研究物体级编辑任务对场景外观产生的相应变化，我们引入了一种深度图引导的场景修复方法，以及一种基于点匹配策略的阴影渲染方法。大量实验表明，我们的新型流程在场景编辑任务中能够产生合理的外观变化，并在新视角合成任务中取得了具有竞争力的渲染质量。
英文摘要：
The 3D scene editing method based on neural implicit field has gained wide attention. It has achieved excellent results in 3D editing tasks. However, existing methods often blend the interaction between objects and scene environment. The change of scene appearance like shadows is failed to be displayed in the rendering view. In this paper, we propose an Object and Scene environment Interaction aware (OSI-aware) system, which is a novel two-stream neural rendering system considering object and scene environment interaction. To obtain illuminating conditions from the mixture soup, the system successfully separates the interaction between objects and scene environment by intrinsic decomposition method. To study the corresponding changes to the scene appearance from object-level editing tasks, we introduce a depth map guided scene inpainting method and shadow rendering method by point matching strategy. Extensive experiments demonstrate that our novel pipeline produce reasonable appearance changes in scene editing tasks. It also achieve competitive performance for the rendering quality in novel-view synthesis tasks.
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。
