Oleg Zabluda's blog
Monday, February 06, 2017
 
Today, in order to facilitate progress in video understanding research, we are introducing YouTube-BoundingBoxes, a...
Today, in order to facilitate progress in video understanding research, we are introducing YouTube-BoundingBoxes, a dataset consisting of 5 million bounding boxes spanning 23 object categories, densely labeling segments from 210,000 YouTube videos. To date, this is the largest manually annotated video dataset containing bounding boxes, which track objects in temporally contiguous frames.

The dataset is designed to be large enough to train large-scale models, and be representative of videos captured in natural settings. Importantly, the human-labelled annotations contain objects as they appear in the real world with partial occlusions, motion blur and natural lighting. Learn more, and get the data, from the Google Research blog, linked below.

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