RESEARCH PAPERYear 2017

Matterport3D: Learning from RGB-D Data in Indoor Environments

Angel X. Chang; Angela Dai; Thomas A. Funkhouser; Maciej Halber; Matthias Nießner; Manolis Savva; Shuran Song; Andy Zeng; Yinda Zhang

Read paper PDF DOI Code

Classification

View four quadrants

Major category: Datasets
Quadrant: Not applicable
Architecture: Not applicable
Prediction paradigm: Not applicable
Subcategories: 3D scene & RGB-D data Multisensor & spatial annotations
Source review status: Verified from primary sources

AT A GLANCE

Contribution

A contribution summary has not been added yet.

Abstract

An abstract has not been added yet.

Affiliations

Not listed in the collection.

BibTeX

@inproceedings{matterport3d,
  author       = {Angel X. Chang and
                  Angela Dai and
                  Thomas A. Funkhouser and
                  Maciej Halber and
                  Matthias Nie{\ss}ner and
                  Manolis Savva and
                  Shuran Song and
                  Andy Zeng and
                  Yinda Zhang},
  title        = {Matterport3D: Learning from {RGB-D} Data in Indoor Environments},
  booktitle    = {3DV},
  pages        = {667--676},
  year         = {2017},
}

Classification

Contribution

Abstract

Affiliations

BibTeX

More in this category

Building Pretraining Data for World Models: An Unreal Engine-Based Pipeline for Action-Conditioned Video Generation

HiFi-UMI: Learning Deployable Manipulation Policies from High-Fidelity UMI Data Alone

How to Instruct Your Robot: Dense Language Annotations Power Robot Policy Learning