Rigid registration is a transformation estimation problem between two point clouds. The two
point clouds captured may partially overlap owing to different viewpoints and acquisition …

Gait analysis is an important tool for the early detection of neurological diseases and for the
assessment of risk of falling in elderly people. The availability of low-cost camera hardware …

The iterative closest point (ICP) algorithm and its variants are a fundamental technique for
rigid registration between two point sets, with wide applications in different areas from …

We present a novel, end-to-end learnable, multiview 3D point cloud registration algorithm.
Registration of multiple scans typically follows a two-stage pipeline: the initial pairwise …

Indoor autonomous navigation refers to the perception and exploration abilities of mobile
agents in unknown indoor environments with the help of various sensors. It is the basic and …

We introduce Nymeria-a large-scale, diverse, richly annotated human motion dataset
collected in the wild with multiple multimodal egocentric devices. The dataset comes with a) …

We propose a self-supervised capsule architecture for 3D point clouds. We compute capsule
decompositions of objects through permutation-equivariant attention, and self-supervise the …

Point clouds are a widely available and canonical data modality which convey the 3D
geometry of a scene. Despite significant progress in classification and segmentation from …

Real-time tracking of 3D hand pose in world space is a challenging problem and plays an
important role in VR interaction. Existing work in this space are limited to either producing …

This paper presents a self-supervised framework for learning to detect robust keypoints for
odometry estimation and metric localisation in radar. By embedding a differentiable point …