Representation Learning for Object Detection from Unlabeled Point Cloud Sequences
A method of representation learning for object detection from unlabeled point cloud sequences is described. The method includes detecting moving object traces from temporally-ordered, unlabeled point cloud sequences. The method also includes extracting a set of moving objects based on the moving object traces detected from the sequence of temporally-ordered, unlabeled point cloud sequences. The method further includes classifying the set of moving objects extracted from on the moving object traces detected from the sequence of temporally-ordered, unlabeled point cloud sequences. The method also includes estimating 3D bounding boxes for the set of moving objects based on the classifying of the set of moving objects.
Researchers
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representation learning for object detection fromunlabeled point cloud sequences
United States of America | Pending -
representation learning for object detection fromunlabeled point cloud sequences
United States of America | Granted | 12,397,817
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