We introduce a novel framework for multiway point cloud mosaicking (named Wednesday)
designed to co-align sets of partially overlapping 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 …

Camera re-localization or absolute pose regression is the centerpiece in numerous
computer vision tasks such as visual odometry, structure from motion (SfM) and SLAM. In …

This paper proposes a deep recurrent Rotation Averaging Graph Optimizer (RAGO) for
Multiple Rotation Averaging (MRA). Conventional optimization-based methods usually fail to …

Recovering 3D structure and camera motion from images has been a long-standing focus of
computer vision research and is known as Structure-from-Motion (SfM). Solutions to this …

Global translation estimation is a highly challenging step in the global structure from motion
(SfM) algorithm. Many existing methods depend solely on relative translations leading to …

Transformation Synchronization is the problem of recovering absolute transformations from
a given set of pairwise relative motions. Despite its usefulness, the problem remains …

Neural Radiance Fields (NeRF) recently emerged as a new paradigm for object
representation from multi-view (MV) images. Yet, it cannot handle multi-scale (MS) images …

We present IRAv3, which is built upon the state-of-the-art rotation averaging method, IRA++,
to push this fundamental task in 3D computer vision one step further. The key observation of …

We introduce an improved solution to the neural image-based rendering problem in
computer vision. Given a set of images taken from a freely moving camera at train time, the …