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Models/DeltaConv

DeltaConv

Reported on 9 benchmarks across 3 tasks · 1 paper · 6 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision9 results

Shape Representation Of 3D Point CloudsonScanObjectNN
Overall Accuracy· 2021-11-16
84.7
best: 97.2 (OmniVec2)
SOTA
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds arXiv:2111.08799
Shape Representation Of 3D Point CloudsonModelNet40
Mean class accuracy· 2021-11-16
91.2
SOTA
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds arXiv:2111.08799
3D Point Cloud ClassificationonScanObjectNN
Overall Accuracy· 2021-11-16
84.7
best: 97.2 (OmniVec2)
SOTA
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds arXiv:2111.08799
3D Point Cloud ClassificationonModelNet40
Mean class accuracy· 2021-11-16
91.2
SOTA
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds arXiv:2111.08799
3D Point Cloud ReconstructiononScanObjectNN
Overall Accuracy· 2021-11-16
84.7
best: 97.2 (OmniVec2)
SOTA
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds arXiv:2111.08799
3D Point Cloud ReconstructiononModelNet40
Mean class accuracy· 2021-11-16
91.2
SOTA
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds arXiv:2111.08799
Shape Representation Of 3D Point CloudsonModelNet40
Overall Accuracy· 2021-11-16
93.8
best: 95.3 (PointGST)
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds arXiv:2111.08799
3D Point Cloud ClassificationonModelNet40
Overall Accuracy· 2021-11-16
93.8
best: 95.3 (PointGST)
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds arXiv:2111.08799
3D Point Cloud ReconstructiononModelNet40
Overall Accuracy· 2021-11-16
93.8
best: 95.3 (PointGST)
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds arXiv:2111.08799