  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/
