12k labelled instances of dogs in-the-wild with 2D keypoint and segmentations.
Dataset released with our ECCV 2020 paper: Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop.
To use StanfordExtra you will require the annotations and the original images files.
- Annotations are available by filling in the Google form. On completion, you will receive an email with the download link.
- Images can be downloaded from the Stanford Dogs webpage. Download the "Images" tar file.
- The
demo.ipynbcode can be adapted work with the full StanfordExtra dataset. To do this, editing the following lines to match with your Stanford Dogs download and your StanfordExtra download:
# edit this to the location of the extracted StanfordDogs tar file (e.g. /.../Images).
img_dir = "sample_imgs"
# edit this to the location of the downloaded full dataset .json
json_loc = "StanfordExtra_sample.json"
You may be interested in our work performing monocular 3D shape and pose reconstruction for animal subjects. If so, check out the following repositories:
If you have a method that makes use of StanfordExtra please do let us know! Community feedback greatly helps us justify future dataset work.
| Version | Date | Comment |
|---|---|---|
| StanfordExtra_V12 | 01 Feb 2021 | Added missing validation set images, added WLDO splits, fixed compressed segmentations |
| StanfordExtra_V1 | 01 Sept 2020 | Original dataset release |
You may also find the other datasets useful for your animal work:
We are also delighted to hear about your animal-related research! Please do visit Ben's webpage if you would like to get in touch.
If you make use of this annotation dataset, please cite the following paper:
@inproceedings{biggs2020wldo,
title={{W}ho left the dogs out?: {3D} animal reconstruction with expectation maximization in the loop},
author={Biggs, Benjamin and Boyne, Oliver and Charles, James and Fitzgibbon, Andrew and Cipolla, Roberto},
booktitle={ECCV},
year={2020}
}
and the Stanford Dog Dataset from which the images are derived:
@inproceedings{KhoslaYaoJayadevaprakashFeiFei_FGVC2011,
author = "Aditya Khosla and Nityananda Jayadevaprakash and Bangpeng Yao and Li Fei-Fei",
title = "Novel Dataset for Fine-Grained Image Categorization",
booktitle = "First Workshop on Fine-Grained Visual Categorization, IEEE Conference on Computer Vision and Pattern Recognition",
year = "2011",
month = "June",
address = "Colorado Springs, CO",
}
(c) Benjamin Biggs, Oliver Boyne, James Charles, Andrew Fitzgibbon and Roberto Cipolla. Department of Engineering, University of Cambridge 2020
By downloading this dataset, you agree to the Creative Commons Attribution-NonCommercial 4.0 International license. This license allows users to use, share and adapt the dataset, so long as credit is given to the authors (e.g. by citation) and the dataset is not used for any commercial purposes.
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