3D Canonicalization
1 papers with code • 0 benchmarks • 0 datasets
3D Canonicalization is the process of estimating a transformation-invariant feature for classification and part segmentation tasks.
Benchmarks
These leaderboards are used to track progress in 3D Canonicalization
Most implemented papers
ConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes
brown-ivl/ConDor
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CVPR 2022
ConDor is a self-supervised method that learns to Canonicalize the 3D orientation and position for full and partial 3D point clouds.
