Pouring a specific amount of liquid is a challenging task. In this paper we develop methods
for robots to use visual feedback to perform closed-loop control for pouring liquids. We …

Establishing dense visual correspondence between multiple images is a fundamental task
in many applications of computer vision and computational photography. Classical …

Recently, feature relation learning has attracted extensive attention in cross-spectral image
patch matching. However, most feature relation learning methods can only extract shallow …

The simultaneous use of images from different spectra can be helpful to improve the
performance of many computer vision tasks. The core idea behind the usage of cross …

Recently, many new applications arose for multi-spectral and hyper-spectral imaging.
Besides modern biometric systems for identity verification, also agricultural and medical …

We propose X-NeRF, a novel method to learn a Cross-Spectral scene representation given
images captured from cameras with different light spectrum sensitivity, based on the Neural …

Cross-spectral imaging provides strong benefits for recognition and detection tasks. Often,
multiple cameras are used for cross-spectral imaging, thus requiring image alignment, or …

Although multispectral and hyperspectral imaging acquisitions are applied in numerous
fields, the existing spectral imaging systems suffer from either low temporal or spatial …

Image patch matching across different spectral domains is more challenging than in a single
spectral domain. We consider the reason is twofold: 1. the weaker discriminative feature …

This letter presents a novel method for the description of multispectral image keypoints. The
method proposed is based on a modified SIFT algorithm. It uses normalized gradients as …