Awesome
Dense Captioning Events in Video - Evaluation Code
Usage
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
Paper
Visit our project page and read our paper for details.
Citation
@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}
}
License
MIT License copyright Ranjay Krishna
Contributions
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