hxwork/OMNet_Pytorch

[ICCV 2021] OMNet: Learning Overlapping Mask for Partial-to-Partial Point Cloud Registration, Pytorch implementation.

29
/ 100
Experimental

This tool helps engineers and researchers accurately align 3D scans of objects, even when the scans only capture part of the object and have missing data. You provide two partial 3D point cloud scans of an object, and it outputs the precise transformation needed to align them perfectly. This is useful for anyone working with 3D scanning, object reconstruction, or robotics.

No commits in the last 6 months.

Use this if you need to precisely align incomplete 3D scans or point clouds of objects that have significant missing data.

Not ideal if you are working with full, complete 3D scans or if you don't require highly robust alignment of partial views.

3D-scanning point-cloud-processing object-reconstruction computer-vision robotics
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 6 / 25

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Stars

39

Forks

2

Language

Python

License

MIT

Last pushed

Jun 08, 2023

Commits (30d)

0

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