Interactive4D: Interactive 4D LiDAR Segmentation

Ilya Fradlin, Idil Esen Zulfikar, Kadir Yilmaz, Theodora Kontogianni, Bastian Leibe

Abstract:

Interactive segmentation has an important role in
facilitating the annotation process of future LiDAR datasets.
Existing approaches sequentially segment individual objects
at each LiDAR scan, repeating the process throughout the
entire sequence, which is redundant and ineffective. In this
work, we propose interactive 4D segmentation, a new paradigm
that allows segmenting multiple objects on multiple LiDAR
scans simultaneously, and Interactive4D, the first interactive
4D segmentation model that segments multiple objects on
superimposed consecutive LiDAR scans in a single iteration by
utilizing the sequential nature of LiDAR data. While performing
interactive segmentation, our model leverages the entire spacetime volume, leading to more efficient segmentation. Operating
on the 4D volume, it directly provides consistent instance IDs
over time and also simplifies tracking annotations. Moreover,
we show that click simulations are crucial for successful model
training on LiDAR point clouds. To this end, we design a
click simulation strategy that is better suited for the characteristics of LiDAR data. To demonstrate its accuracy and
effectiveness, we evaluate Interactive4D on multiple LiDAR
datasets, where Interactive4D achieves a new state-of-the-art
by a large margin.