amazon.science computer vision deep learning machine learning
Airborne Object Tracking (AOT) is a collection of 4,943 flight sequences of around 120 seconds each, collected at 10 Hz in diverse conditions. There are 5.9M+ images and 3.3M+ 2D annotations of airborne objects in the sequences. There are 3,306,350 frames without labels as they contain no airborne objects. For images with labels, there are on average 1.3 labels per image. All airborne objects in the dataset are labelled.
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Community Data License Agreement – Permissive, Version 1.0 https://cdla.dev/permissive-1-0/
https://www.aicrowd.com/challenges/airborne-object-tracking-challenge
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airborne-object-tracking-challenge@amazon.com
Airborne Object Tracking Dataset was accessed on DATE
from https://registry.opendata.aws/airborne-object-tracking.
arn:aws:s3:::airborne-obj-detection-challenge-training
us-east-1
aws s3 ls --no-sign-request s3://airborne-obj-detection-challenge-training/