Computer vision for autonomous vehicles: Problems, datasets and state of the art

J Janai, F Güney, A Behl, A Geiger - Foundations and trends® …, 2020 - nowpublishers.com
Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

Multi-view stereo: A tutorial

Y Furukawa, C Hernández - Foundations and trends® in …, 2015 - nowpublishers.com
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 …

Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction

P Wang, L Liu, Y Liu, C Theobalt, T Komura… - ar**: Toward the robust-perception age
C Cadena, L Carlone, H Carrillo, Y Latif… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
Simultaneous localization and map** (SLAM) consists in the concurrent construction of a
model of the environment (the map), and the estimation of the state of the robot moving …

Learning a multi-view stereo machine

A Kar, C Häne, J Malik - Advances in neural information …, 2017 - proceedings.neurips.cc
We present a learnt system for multi-view stereopsis. In contrast to recent learning based
methods for 3D reconstruction, we leverage the underlying 3D geometry of the problem …

Deep marching cubes: Learning explicit surface representations

Y Liao, S Donne, A Geiger - Proceedings of the IEEE …, 2018 - openaccess.thecvf.com
Existing learning based solutions to 3D surface prediction cannot be trained end-to-end as
they operate on intermediate representations (eg, TSDF) from which 3D surface meshes …

A survey of surface reconstruction from point clouds

M Berger, A Tagliasacchi, LM Seversky… - Computer graphics …, 2017 - Wiley Online Library
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 …

Hierarchical surface prediction for 3d object reconstruction

C Häne, S Tulsiani, J Malik - 2017 International Conference on …, 2017 - ieeexplore.ieee.org
Recently, Convolutional Neural Networks have shown promising results for 3D geometry
prediction. They can make predictions from very little input data such as a single color …