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Models/PointStack

PointStack

Reported on 12 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 Vision12 results

Shape Representation Of 3D Point CloudsonScanObjectNN
Mean Accuracy· 2022-05-20
86.2
best: 93.8 (GPSFormer)
SOTA
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling arXiv:2205.09962
Shape Representation Of 3D Point CloudsonScanObjectNN
Overall Accuracy· 2022-05-20
87.2
best: 97.2 (OmniVec2)
SOTA
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling arXiv:2205.09962
3D Point Cloud ClassificationonScanObjectNN
Mean Accuracy· 2022-05-20
86.2
best: 93.8 (GPSFormer)
SOTA
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling arXiv:2205.09962
3D Point Cloud ClassificationonScanObjectNN
Overall Accuracy· 2022-05-20
87.2
best: 97.2 (OmniVec2)
SOTA
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling arXiv:2205.09962
3D Point Cloud ReconstructiononScanObjectNN
Mean Accuracy· 2022-05-20
86.2
best: 93.8 (GPSFormer)
SOTA
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling arXiv:2205.09962
3D Point Cloud ReconstructiononScanObjectNN
Overall Accuracy· 2022-05-20
87.2
best: 97.2 (OmniVec2)
SOTA
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling arXiv:2205.09962
Shape Representation Of 3D Point CloudsonModelNet40
Mean Accuracy· 2022-05-20
89.6
best: 92.4 (ULIP + PointMLP)
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling arXiv:2205.09962
Shape Representation Of 3D Point CloudsonModelNet40
Overall Accuracy· 2022-05-20
93.3
best: 95.3 (PointGST)
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling arXiv:2205.09962
3D Point Cloud ClassificationonModelNet40
Mean Accuracy· 2022-05-20
89.6
best: 92.4 (ULIP + PointMLP)
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling arXiv:2205.09962
3D Point Cloud ClassificationonModelNet40
Overall Accuracy· 2022-05-20
93.3
best: 95.3 (PointGST)
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling arXiv:2205.09962
3D Point Cloud ReconstructiononModelNet40
Mean Accuracy· 2022-05-20
89.6
best: 92.4 (ULIP + PointMLP)
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling arXiv:2205.09962
3D Point Cloud ReconstructiononModelNet40
Overall Accuracy· 2022-05-20
93.3
best: 95.3 (PointGST)
Advanced Feature Learning on Point Clouds using Multi-resolution Features and Learnable Pooling arXiv:2205.09962