Awesome

StanfordExtra

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.

• Project page
• Paper

Download

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.

Installation

• The demo.ipynb code 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"

Methods using StanfordExtra

You may be interested in our work performing monocular 3D shape and pose reconstruction for animal subjects. If so, check out the following repositories:

• Who Left the Dogs Out?
• SMALify

If you have a method that makes use of StanfordExtra please do let us know! Community feedback greatly helps us justify future dataset work.

Versioning

Comments

You may also find the other datasets useful for your animal work:

• Animal Pose Dataset
• RGBD-Dog Dataset
• BADJA

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.

Acknowledgements

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",
}

Licensing

(c) Benjamin Biggs, Oliver Boyne, James Charles, Andrew Fitzgibbon and Roberto Cipolla. Department of Engineering, University of Cambridge 2020

As of 02-NOV-2024, this dataset is now MIT licensed. Enjoy!

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.