ASSIST：面向可扩展且逼真室内仿真的交互式场景节点
ASSIST: Interactive Scene Nodes for Scalable and Realistic Indoor Simulation
AI总结：
本文提出ASSIST，一种对象级神经辐射场，通过新颖的场景节点数据结构实现交互式编辑和组合渲染，支持对象查询、增删改等操作，实现可扩展且逼真的室内仿真。
摘要：
我们提出ASSIST，一种对象级神经辐射场，作为组合且逼真仿真的全景表示。我们方法的核心是一种新颖的场景节点数据结构，它以统一的方式存储每个对象的信息，允许在场景内和跨场景设置中进行在线交互。通过结合可微神经网络以及相关的边界框和语义特征，所提出的结构保证了在独立对象上进行用户友好的交互，以扩展新颖视图仿真。场景中的对象可以通过鼠标/键盘控制或语言指令进行查询、添加、复制、删除、变换或交换。实验证明了所提出方法的有效性，通过交互式编辑和组合渲染可以实现可扩展的逼真仿真，并以3D一致的方式生成彩色图像、深度图像和全景分割掩码。
英文摘要：
We present ASSIST, an object-wise neural radiance field as a panoptic representation for compositional and realistic simulation. Central to our approach is a novel scene node data structure that stores the information of each object in a unified fashion, allowing online interaction in both intra- and cross-scene settings. By incorporating a differentiable neural network along with the associated bounding box and semantic features, the proposed structure guarantees user-friendly interaction on independent objects to scale up novel view simulation. Objects in the scene can be queried, added, duplicated, deleted, transformed, or swapped simply through mouse/keyboard controls or language instructions. Experiments demonstrate the efficacy of the proposed method, where scaled realistic simulation can be achieved through interactive editing and compositional rendering, with color images, depth images, and panoptic segmentation masks generated in a 3D consistent manner.
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。
