SnapshotNet: Self-supervised Feature Learning for Point Cloud Data Segmentation Using Minimal Labeled Data. (arXiv:2201.04833v1 [cs.CV])

Manually annotating complex scene point cloud datasets is both costly and
error-prone. To reduce the reliance on labeled data, a new model called
SnapshotNet is proposed as a self-supervised feature learning approach, which
directly works on the unlabeled point cloud data of a complex 3D scene. The
SnapshotNet pipeline includes three stages. In the snapshot capturing stage,
snapshots, which are defined as local collections of points, are sampled from
the point cloud scene. A snapshot could be a view of …

arxiv cloud cloud data cv data learning segmentation