Unmanned aerial vehicle (UAV) images have gained extensive attention in varying fields,
and the Structure from Motion (SfM) technique has become the gold standard for aerial …

This paper is intended to pave the way for new researchers in the field of robotics and
autonomous systems, particularly those who are interested in robot localization and …

With the advent of convolutional neural networks, stereo matching algorithms have recently
gained tremendous progress. However, it remains a great challenge to accurately extract …

Recent work has shown that CNN-based depth and ego-motion estimators can be learned
using unlabelled monocular videos. However, the performance is limited by unidentified …

Matching local features across images is a fundamental problem in computer vision.
Targeting towards high accuracy and efficiency, we propose Seeded Graph Matching …

Incorporating smoothness constraints into feature matching is known to enable ultra-robust
matching. However, such formulations are both complex and slow, making them unsuitable …

We propose MAGSAC++ and Progressive NAPSAC sampler, P-NAPSAC in short. In
MAGSAC++, we replace the model quality and polishing functions of the original method by …

The structure from motion (SfM) problem in computer vision is to recover the three-
dimensional (3D) structure of a stationary scene from a set of projective measurements …

In this work we present a monocular visual odometry (VO) algorithm which leverages
geometry-based methods and deep learning. Most existing VO/SLAM systems with superior …

We present an approach to robust estimation of fundamental matrices from noisy data
contaminated by outliers. The problem is cast as a series of weighted homogeneous least …