论文标题
辐射场的互动分割
Interactive Segmentation of Radiance Fields
论文作者
论文摘要
辐射场（RF）很受欢迎，可以代表新视图综合的随意捕获场景及其以外的几种应用。个人空间上的混合现实需要理解和操纵为RFS表示的场景，并将对象的语义分割为重要步骤。先前的细分工作表现出希望，但不要扩展到具有多样化的复杂物体。我们提出了ISRF方法，以交互性段对象具有精细的结构和外观。使用蒸馏语义特征与最近的邻居特征匹配可以识别高信心种子区域。联合空间语义空间中的双边搜索生长该区域以恢复精确的分割。我们显示了从RFS分割对象并将其组合到另一个场景，外观等的最新结果，以及其他人可以使用的交互式分割工具。 项目页面：https：//rahul-goel.github.io/isrf/
Radiance Fields (RF) are popular to represent casually-captured scenes for new view synthesis and several applications beyond it. Mixed reality on personal spaces needs understanding and manipulating scenes represented as RFs, with semantic segmentation of objects as an important step. Prior segmentation efforts show promise but don't scale to complex objects with diverse appearance. We present the ISRF method to interactively segment objects with fine structure and appearance. Nearest neighbor feature matching using distilled semantic features identifies high-confidence seed regions. Bilateral search in a joint spatio-semantic space grows the region to recover accurate segmentation. We show state-of-the-art results of segmenting objects from RFs and compositing them to another scene, changing appearance, etc., and an interactive segmentation tool that others can use. Project Page: https://rahul-goel.github.io/isrf/
