A framework for analyzing computer vision models with simulated data

Last update: Jan 01, 2023

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Deep Learning 3db

Overview

3DB: A framework for analyzing computer vision models with simulated data

Paper

Quickstart guide

Blog post

Installation

Follow instructions on: https://github.com/3db/installers

Complete demo

For detailed, step by step demonstration of the usage of the framework, please visit: https://github.com/3db/demo

Documentation

You can find in-depth documentation for the package here, including a quickstart guide, an explanation on the internal layout of the package, as well as guides for extending 3DB to new modalities, tasks, and output formats.

Primer data

We offer data for users to quickly get started 3DB and reproduce the results of the paper mentioned below. It is available on dropbox at this link: https://www.dropbox.com/s/2gdprhp8jvku4zf/threedb_starting_kit.tar.gz?dl=0. (One can use wget to download it).

It contains:

3D models
Environments: our studio and HDRI backgrounds
Replacement textures to use with threedb.controls.blender.material
Licensing/credits for the data

Citation

If you find 3DB helpful, please cite it as:

@inproceedings{leclerc2021three,
    title={3DB: A Framework for Debugging Computer Vision Models},
    author={Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry},
    year={2021},
    booktitle={Arxiv preprint arXiv:2106.03805}
}

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A framework for analyzing computer vision models with simulated data

Related tags

Overview

3DB: A framework for analyzing computer vision models with simulated data

Installation

Complete demo

Documentation

Primer data

Citation

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0.09(Jun 8, 2021)

0.0.8(Jun 7, 2021)

0.0.7(Jun 7, 2021)

0.0.6(May 22, 2021)

0.0.5(May 22, 2021)

0.0.4(May 22, 2021)

0.0.3(May 22, 2021)

0.0.2(May 22, 2021)

Owner

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