REVNET is a rotation-equivariant point cloud completion model using Vector Neuron anchors and transformers that outperforms prior methods on synthetic MVP data and matches non-equivariant baselines on real KITTI data without input alignment.
IEEE TPAMI45(1), 852–867 (Jan 2023)
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REVNET: Rotation-Equivariant Point Cloud Completion via Vector Neuron Anchor Transformer
REVNET is a rotation-equivariant point cloud completion model using Vector Neuron anchors and transformers that outperforms prior methods on synthetic MVP data and matches non-equivariant baselines on real KITTI data without input alignment.