Short description of dataset and use case(s): The YouTube-8M Segments dataset is an extension of the YouTube-8M dataset with human-verified segment annotations. In addition to annotating videos, we would like to temporally localize the entities in the videos, i.e., find out when the entities occur.
We collected human-verified labels on about 237K segments on 1000 classes from the validation set of the YouTube-8M dataset. Each video will again come with time-localized frame-level features so classifier predictions can be made at segment-level granularity. We encourage researchers to leverage the large amount of noisy video-level labels in the training set to train models for temporal localization.
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Our team has a limited bandwidth to implement all requested dataset. But do not hesitate to send a pull request if you already implemented this dataset.
We collected human-verified labels on about 237K segments on 1000 classes from the validation set of the YouTube-8M dataset. Each video will again come with time-localized frame-level features so classifier predictions can be made at segment-level granularity. We encourage researchers to leverage the large amount of noisy video-level labels in the training set to train models for temporal localization.
Folks who would also like to see this dataset in
tensorflow/datasets
, please thumbs-up so the developers can know which requests to prioritize.And if you'd like to contribute the dataset (thank you!), see our guide to adding a dataset.