VideoCC is a dataset containing (video-URL, caption) pairs for training video-text machine learning models.
It is created using an automatic pipeline starting from the Conceptual Captions Image-Captioning Dataset.
More details are available in this paper at ECCV 2022. Please cite the paper if you use or discuss this dataset in your work.
@inproceedings{nagrani2022learning,
title = {Learning Audio Video Modalities from Image Captions},
author = {Nagrani, Arsha and Hongsuck Seo, Paul and Seybold, Bryan, and Hauth Anja, and Santiago, Manen, and Chen, Sun and Schmid, Cordelia},
booktitle = {ECCV},
year = {2022},
}
The data is provided here(note the file should start downloading immediately) as a single CSV file with the following columns:
Video URL, Start timestamp (microseconds), End timestamp(microseconds), Caption.
The data will not be exactly the same as the dataset used to train models in the paper but should be similar. Note that some sections of YouTube videos might contain static frames that are panned in or out. These can be filtered out using a motion filtering tool.