Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving
and transportation systems to digitize and synergize connected automated vehicles …

Analysing 88 sources published from 2011 to 2021, this article presents a first systematic
review of the computer vision-based analysis of buildings and the built environment. Its aim …

Large-scale synthetic traffic image datasets have been widely used to make compensate for
the insufficient data in real world. However, the mismatch in domain distribution between …

The goal of this review is to present a detailed and comprehensive description of the
published work from the past decade regarding methods of improved material, geometric …

We propose GroundUp, the first sketch-based ideation tool for 3D city massing of urban
areas. We focus on early-stage urban design, where sketching is a common tool and the …

Digital images are a particular type of data. They have numerous applications. Taking into
account current challenges and trends, image compression and protection have to be …

With the development of photogrammetry, digital city, and metaverse, the 3-D representation
of urban buildings has attracted more and more attention. As the main form of the 3-D urban …

To improve their adaptability to various kinds of driving situations, deep learning-based
vision algorithms need images from rare scenes, such as extreme weather conditions and …

Diverse and large-high-quality data are essential to the deep learning algorithms for
autonomous driving. However, manual data collection in intricate traffic scenarios is …

Abstract 3D urban building modeling is a vital foundational step for building Digital Twins
and Smart Cities. In response to existing challenges, such as high time costs, complex …