Overview

The StanfordExtra dataset contains 12k labelled instances of dogs in-the-wild with 2D keypoint and segmentations.It released with the ECCV 2020 paper: Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop.

Instruction

All annotations, segmentations and metadata are sourced in a single .json file for ease of download. However, you will also need to download the Stanford Dogs dataset to access the raw images.
For segmentation decoding, install pycocotools

python -m pip install "git+https://github.com/philferriere/cocoapi.git#subdirectory=PythonAPI"

The demo.ipynb code is trivial to adapt to work with the full StanfordExtra dataset, by 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"

Citation

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",
}

License

CC BY-NC-SA 4.0