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 …

Image-based 3D reconstruction of civil infrastructure is an emerging topic that is gaining
significant interest both in the scientific and commercial sectors of the construction industry …

This paper addresses the challenge of reconstructing 3D indoor scenes from multi-view
images. Many previous works have shown impressive reconstruction results on textured …

Recently, implicit neural representations have gained popularity for learning-based 3D
reconstruction. While demonstrating promising results, most implicit approaches are limited …

Stereo depth estimation relies on optimal correspondence matching between pixels on
epipolar lines in the left and right images to infer depth. In this work, we revisit the problem …

This work presents a Multi-View Stereo system for robust and efficient dense modeling from
unstructured image collections. Our core contributions are the joint estimation of depth and …

We present DeepMVS, a deep convolutional neural network (ConvNet) for multi-view stereo
reconstruction. Taking an arbitrary number of posed images as input, we first produce a set …

We introduce SceneScript, a method that directly produces full scene models as a sequence
of structured language commands using an autoregressive, token-based approach. Our …

This paper proposes a deep neural architecture, PlaneRCNN, that detects and reconstructs
piecewise planar regions from a single RGB image. PlaneRCNN employs a variant of Mask …

This paper proposes a deep neural network (DNN) for piece-wise planar depthmap
reconstruction from a single RGB image. While DNNs have brought remarkable progress to …