Accurately building height estimation from remote sensing imagery is an important and
challenging task. However, the existing shadow-based building height estimation methods …

Estimating the height of buildings and vegetation in single aerial images is a challenging
problem. A task-focused Deep Learning (DL) model that combines architectural features …

The increasing importance of three-dimensional (3D) city modelling is linked to these data's
different applications and advantages in many domains. Images and Light Detection and …

Building heights play a vital role in the field of urban morphology and allied applications.
Recently there is a push to retrieve building heights from the space borne sensors. NASA's …

Height estimation from single images, strictly speaking, is an ill-posed problem. However,
recently, it is shown that it is both possible and feasible to learn a mapping from image …

Airborne laser scanning point cloud semantic labeling, which aims to identify the category of
each point, plays a significant role in many applications, such as forest observing, powerline …

A novel framework for 3D reconstruction of buildings based on a single off-nadir satellite
image is proposed in this paper. Compared with the traditional methods of reconstruction …

Deep learning provides a powerful new approach to many computer vision tasks. Height
prediction from aerial images is one of those tasks which benefited greatly from the …

In this paper, a different approach based on convolutional neural networks (CNNs) is
proposed to generate digital surface model (DSM) from a single high-resolution satellite …

Recently, remote sensing satellite image analysis has received significant attention from geo-
information scientists. However, the current geo-information systems lack automatic …