Moving vehicles in satellite videos can be detected at 98.8 frames per second with 89.7% F1 using a sparse point cloud network trained on self-evolving pseudo-labels, with no manual annotations.
Moving object detection in satellite videos via spatial-temporal tensor model and weighted schatten p-norm minimization,
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Highly Efficient and Unsupervised Framework for Moving Object Detection in Satellite Videos
Moving vehicles in satellite videos can be detected at 98.8 frames per second with 89.7% F1 using a sparse point cloud network trained on self-evolving pseudo-labels, with no manual annotations.