This paper presents a study on the usage landscape of augmented reality (AR) and virtual
reality (VR) in the architecture, engineering and construction sectors, and proposes a …

Abstract 3D point cloud data obtained from laser scans, images, and videos are able to
provide accurate and fast records of the 3D geometries of construction-related objects. Thus …

The research progress in multimodal learning has grown rapidly over the last decade in
several areas, especially in computer vision. The growing potential of multimodal data …

In this paper, we present a novel cross-consistency based semi-supervised approach for
semantic segmentation. Consistency training has proven to be a powerful semi-supervised …

Shape priors learned from data are commonly used to reconstruct 3D objects from partial or
noisy data. Yet no such shape priors are available for indoor scenes, since typical 3D …

For many fundamental scene understanding tasks, it is difficult or impossible to obtain per-
pixel ground truth labels from real images. We address this challenge by introducing …

We introduce Infinigen, a procedural generator of photorealistic 3D scenes of the natural
world. Infinigen is entirely procedural: every asset, from shape to texture, is generated from …

We introduce Replica, a dataset of 18 highly photo-realistic 3D indoor scene reconstructions
at room and building scale. Each scene consists of a dense mesh, high-resolution high …

You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

Implicit neural networks have been successfully used for surface reconstruction from point
clouds. However, many of them face scalability issues as they encode the isosurface …