First, clone this repository and make sure that all the submodules are also cloned properly.

git clone --recursive https://github.com/ranjaykrishna/densevid_eval.git

Next, download the dataset using

./download.sh

Finally, test that the evaluator runs by testing it on our sample_submission.json file by calling:

python evaluate.py

You are now all set to produce your own dense captioning results for videos and use this code to evaluate your mode:

python evaluate.py -s YOUR_SUBMISSION_FILE.JSON

Visit our project page and read our paper for details.

@inproceedings{krishna2017dense,
    title={Dense-Captioning Events in Videos},
    author={Krishna, Ranjay and Hata, Kenji and Ren, Frederic and Fei-Fei, Li and Niebles, Juan Carlos},
    booktitle={ArXiv},
    year={2017}
}

MIT License copyright Ranjay Krishna

Feel free to send pull requests to help write example code, contribute patches, document methods, etc. You can reach me through:

twitter: @RanjayKrishna

email: ranjaykrishna [at] stanford [dot] edu