Scene perception and trajectory forecasting are two fundamental challenges that are crucial
to a safe and reliable autonomous driving (AD) system. However, most proposed methods …

Abstract 3D scene flow estimation aims to estimate point-wise motions between two
consecutive frames of point clouds. Superpoints, ie, points with similar geometric features …

A point cloud is a set of data points in space. Point cloud registration is the process of
aligning two or more 3D point clouds collected from different locations of the same scene …

Point cloud registration is the process of aligning point clouds collected at different locations
of the same scene, which transforms the data into a common coordinate system and forms …

Scene flow estimation is a long-standing problem in computer vision, where the goal is to
find the 3D motion of a scene from its consecutive observations. Recently, there have been …

Scene flow estimation provides the fundamental motion perception of a dynamic scene,
which is of practical importance in many computer vision applications. In this paper, we …

Scene flow estimation which aims to predict per-point 3D displacements of dynamic scenes
is a fundamental task in the computer vision field. However previous works commonly suffer …

We tackle the task of scene flow estimation from point clouds. Given a source and a target
point cloud, the objective is to estimate a translation from each point in the source point …

As a low-level task of 3D perception, scene flow is a fundamental representation of dynamic
scenes and provides non-rigid motion descriptions for the objects in the 3D environment …

Understanding the motion behavior of dynamic environments is vital for autonomous driving,
leading to increasing attention in class-agnostic motion prediction in LiDAR point clouds …