Abstract Three-dimensional (3D) reconstruction techniques have been used to obtain the 3D
representations of objects in civil engineering in the form of point cloud models, mesh …

This tutorial presents a hands-on view of the field of multi-view stereo with a focus on
practical algorithms. Multi-view stereo algorithms are able to construct highly detailed 3D …

Denoising diffusion models (DDMs) have shown promising results in 3D point cloud
synthesis. To advance 3D DDMs and make them useful for digital artists, we require (i) high …

Neural Radiance Fields (NeRF) are a rapidly growing area of research with wide-ranging
applications in computer vision, graphics, robotics, and more. In order to streamline the …

Neural surface reconstruction has been shown to be powerful for recovering dense 3D
surfaces via image-based neural rendering. However, current methods struggle to recover …

We propose a method to allow precise and extremely fast mesh extraction from 3D Gaussian
Splatting. Gaussian Splatting has recently become very popular as it yields realistic …

Abstract 3D scene understanding plays a vital role in vision-based autonomous driving.
While most existing methods focus on 3D object detection, they have difficulty describing …

Abstract We present Text2Room, a method for generating room-scale textured 3D meshes
from a given text prompt as input. To this end, we leverage pre-trained 2D text-to-image …

The combination of deep learning, artist-curated scans, and Implicit Functions (IF), is
enabling the creation of detailed, clothed, 3D humans from images. However, existing …

We present ScanNet++, a large-scale dataset that couples together capture of high-quality
and commodity-level geometry and color of indoor scenes. Each scene is captured with a …