Three-dimensional (3-D) urban models are an integral part of numerous applications, such
as urban planning and performance simulation, map** and visualization, emergency …

To the best of our knowledge, the most recent light detection and ranging (lidar)-based
surveys have been focused only on specific applications such as reconstruction and …

A central goal of visual recognition is to understand objects and scenes from a single image.
2D recognition has witnessed tremendous progress thanks to large-scale learning and …

This paper focuses on semantic scene completion, a task for producing a complete 3D voxel
representation of volumetric occupancy and semantic labels for a scene from a single-view …

The area of surface reconstruction has seen substantial progress in the past two decades.
The traditional problem addressed by surface reconstruction is to recover the digital …

We propose a novel framework for reconstructing lightweight polygonal surfaces from point
clouds. Unlike traditional methods that focus on either extracting good geometric primitives …

With the increasing reliance of self-driving and similar robotic systems on robust 3D vision,
the processing of LiDAR scans with deep convolutional neural networks has become a trend …

We present an automatic approach for the reconstruction of parametric 3D building models
from indoor point clouds. While recently developed methods in this domain focus on mere …

We present a novel method for reconstructing parametric, volumetric, multi-story building
models from unstructured, unfiltered indoor point clouds with oriented normals by means of …

In this paper, we propose a novel 3D-RecGAN approach, which reconstructs the complete
3D structure of a given object from a single arbitrary depth view using generative adversarial …