YouCook2 Dataset Home Explore Download Leaderboard

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Please read the README file before download.
Annotations (single .json file): Train+Val
Recipe ID/type: ID-type pairs
Splits: Train+Val+Test
Scripts: Download Scripts
Frame-wise ResNet feature (.csv, 23.9GB): Train+Val+Test
Frame-wise ResNet feature (.dat, 11.2GB): Train+Val+Test
All-in-one (35.1GB): YouCook2

Download (YouCook2-BB)

[05/07/2019] Reformatted the annotation JSON files. Augmented the initial release with 3.5% more annotations. See the bottom of the code repo for more details.
Please read the README file inside the annotation pack.
Annotations (1.2MB): YouCook2-BB
Region proposals and features see the code repo.

Download (others)

We provide both deep appearance (RGB) and motion (optic flow) feature extracted from TSN at our DenseCap repo. See our CVPR 2018 paper for more details.

Citation

We introduced YouCook2 dataset in our AAAI 2018 paper on video procedure segmentation. Please cite the following if you find the dataset useful:
  @inproceedings{ZhXuCoCVPR18,
    author={Zhou, Luowei and Xu, Chenliang and Corso, Jason J},
    title = {Towards Automatic Learning of Procedures From Web Instructional Videos},
    booktitle = {AAAI Conference on Artificial Intelligence},
    pages={7590--7598},
    year = {2018},
    url = {https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/17344}
  }
           

The bounding box annotation comes from our BMVC 2018 paper on weakly-supervised video object grounding. Please cite the following if you find the annotation useful:
  @inproceedings{ZhLoCoBMVC18,
    author={Zhou, Luowei and Louis, Nathan and Corso, Jason J},
    title={Weakly-Supervised Video Object Grounding from Text by Loss Weighting and Object Interaction},
    booktitle = {British Machine Vision Conference},
    year = {2018},
    url = {http://bmvc2018.org/contents/papers/0070.pdf}
  }