This paper presents a coherent framework for automated unmanned aircraft system based
inspections of large bridges to facilitate an automated condition assessment. Modern …

We study the problem of generating plausible interpretations of a scene from a collection of
line segments automatically extracted from a single indoor image. We show that we can …

In this paper we tackle the problem of learning Structure-from-Motion (SfM) through the use
of graph attention networks. SfM is a classic computer vision problem that is solved though …

Separable nonlinear least squares (SNLLS) problems have attracted interest in a wide
range of research fields such as machine learning, computer vision, and signal processing …

Effective fault detection and diagnosis (FDD) is crucial in modern industry applications, but
developing accurate and interpretable FDD models for complex processes remains a …

Existing deep methods produce highly accurate 3D reconstructions in stereo and multiview
stereo settings, ie, when cameras are both internally and externally calibrated. Nevertheless …

This paper investigates algorithms for matrix factorization when some or many components
are missing, a problem that arises frequently in computer vision and pattern recognition. We …

Current Internet transport protocols are being revisited in an attempt to respond to traffic
growth in size, diversity and the emergence of new applications. Designed to reduce Web …

Bundle adjustment is a key component in practically all available Structure from Motion
systems. While it is crucial for achieving accurate reconstruction, convergence to the right …

Variable Projection (VarPro) is a framework to solve optimization problems efficiently by
optimally eliminating a subset of the unknowns. It is in particular adapted for Separable …