Exploring Video Rhythm and Sequence
Newly Released: YouTube-8M Segments Dataset for AI Video Prediction
Google has made a significant stride in the field of AI research by publishing the YouTube-8M Segments dataset. This dataset, designed to help train AI systems to predict video content, is now available for researchers to use.
The YouTube-8M Segments dataset consists of a portion of the full videos from the original YouTube-8M dataset, published by Google earlier. It contains 237,000 five-second video segments, each annotated with time-localized labels. Each folder in the dataset contains the video segment and its corresponding annotation file in JSON format.
The annotations provide human-created labels indicating a video's content at five-second intervals. This is crucial as the full YouTube-8M dataset lacked enough annotations for an AI system to predict what would happen next in a video.
The dataset is organised in a manner that makes it easy to use. Each video segment is contained within a separate folder. Researchers are encouraged to cite the dataset in their work and can access it through Google Drive. Google provides a script to download the entire dataset from Google Drive.
The YouTube-8M Segments dataset is licensed under the Creative Commons Attribution 4.0 International License and is provided free of charge. It is intended for non-commercial research purposes only.
Advancements in video classification algorithms have been made due to the previous publication of the full YouTube-8M dataset by Google. The YouTube-8M Segments dataset is intended to enable AI systems to better understand and predict video sequences, thereby pushing the boundaries of what AI can achieve in the realm of video content analysis.
Google announced the release of the YouTube-8M Segments dataset on the Google AI Blog in 2018. Researchers are invited to explore this valuable resource and contribute to the ongoing advancements in the field of AI and video prediction.
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