This repository contains:
for the the following paper:
Taskonomy: Disentangling Task Transfer Learning (CVPR 2018, Best Paper Award)
Amir Zamir, Alexander Sax*, William Shen*, Leonidas Guibas, Jitendra Malik, Silvio Savarese.
| TASK BANK | DATASET |
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The taskbank folder contains information about our pretrained models, and scripts to download them. There are sample outputs, and links to live demos. |
The data folder contains information and statistics about the dataset, some sample data, and instructions for how to download the full dataset. |
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| Task affinity analyses and results | Website |
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| This folder contains the raw and normalized data used for measuring task affinities. | The webpage of the project with links to assets and demos. |
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If you find the code, models, or data useful, please cite this paper:
@inproceedings{zamir2018taskonomy,
title={Taskonomy: Disentangling Task Transfer Learning},
author={Zamir, Amir R and Sax, Alexander and and Shen, William B and Guibas, Leonidas and Malik, Jitendra and Savarese, Silvio},
booktitle={2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2018},
organization={IEEE}
}