PointTransformerX is a fully PyTorch-native 3D point cloud transformer backbone that reaches 98.7% of PointTransformer V3 accuracy on ScanNet using 79.2% fewer parameters, 1.6x faster inference, and only 253 MB memory while running natively on NVIDIA, AMD, and CPU hardware.
Pointcept: A codebase for point cloud perception research.https://github.com/ Pointcept/Pointcept
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PointTPA uses serialization-based neighborhood grouping and a dynamic parameter projector to adapt network weights per scene patch, reaching 78.4% mIoU on ScanNet with under 2% added parameters.
citing papers explorer
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PointTransformerX: Portable and Efficient 3D Point Cloud Processing without Sparse Algorithms
PointTransformerX is a fully PyTorch-native 3D point cloud transformer backbone that reaches 98.7% of PointTransformer V3 accuracy on ScanNet using 79.2% fewer parameters, 1.6x faster inference, and only 253 MB memory while running natively on NVIDIA, AMD, and CPU hardware.
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PointTPA: Dynamic Network Parameter Adaptation for 3D Scene Understanding
PointTPA uses serialization-based neighborhood grouping and a dynamic parameter projector to adapt network weights per scene patch, reaching 78.4% mIoU on ScanNet with under 2% added parameters.