Robust principal component analysis (RPCA) via decomposition into low-rank plus sparse
matrices offers a powerful framework for a large variety of applications such as image …

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 …

This paper addresses the problem of robust and efficient relative rotation averaging in the
context of large-scale Structure from Motion. Relative rotation averaging finds global or …

In this paper we explore the role of duality principles within the problem of rotation
averaging, a fundamental task in a wide range of computer vision applications. In its …

We introduce a novel framework for multiway point cloud mosaicking (named Wednesday)
designed to co-align sets of partially overlap** point clouds--typically obtained from 3D …

We propose a novel hierarchical approach for multiple rotation averaging, dubbed HARA.
Our method incrementally initializes the rotation graph based on a hierarchy of triplet …

This paper addresses the problem of rigid-motion synchronization (aka motion averaging) in
the Special Euclidean Group SE (3), which finds application in structure-from-motion and …

Star trackers are primarily optical devices that are used to estimate the attitude of a
spacecraft by recognising and tracking star patterns. Currently, most star trackers use …

Reconstructing the 3D model of a physical object typically requires us to align the depth
scans obtained from different camera poses into the same coordinate system. Solutions to …

We propose a new algorithm to solve optimization problems of the form $\min f (X) $ for a
smooth function $ f $ under the constraints that $ X $ is positive semidefinite and the …