StanfordExtra
许可协议:
CC BY-NC-SA 4.0
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
report
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