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Models/GPr-Net + Hyp (512)

GPr-Net + Hyp (512)

Reported on 24 benchmarks across 3 tasks · 1 paper

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

Computer Vision24 results

Shape Representation Of 3D Point CloudsonModelNet40 10-way (20-shot)
Overall Accuracy· 2023-04-12
73.8
best: 96.5 (ReCon++)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
Shape Representation Of 3D Point CloudsonModelNet40 10-way (20-shot)
Standard Deviation· 2023-04-12
2
best: 13.5 (PointNet)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
Shape Representation Of 3D Point CloudsonModelNet40 5-way (10-shot)
Overall Accuracy· 2023-04-12
81.1
best: 98 (PointGPT)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
Shape Representation Of 3D Point CloudsonModelNet40 5-way (10-shot)
Standard Deviation· 2023-04-12
1.5
best: 16 (PointNet++)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
Shape Representation Of 3D Point CloudsonModelNet40 10-way (10-shot)
Overall Accuracy· 2023-04-12
71.6
best: 95 (Point-JEPA)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
Shape Representation Of 3D Point CloudsonModelNet40 10-way (10-shot)
Standard Deviation· 2023-04-12
1.1
best: 13.5 (PointNet)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
Shape Representation Of 3D Point CloudsonModelNet40 5-way (20-shot)
Overall Accuracy· 2023-04-12
82.7
best: 99.5 (ReCon++)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
Shape Representation Of 3D Point CloudsonModelNet40 5-way (20-shot)
Standard Deviation· 2023-04-12
1.3
best: 15.5 (PointNet)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ClassificationonModelNet40 10-way (20-shot)
Overall Accuracy· 2023-04-12
73.8
best: 96.5 (ReCon++)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ClassificationonModelNet40 10-way (20-shot)
Standard Deviation· 2023-04-12
2
best: 13.5 (PointNet)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ClassificationonModelNet40 5-way (10-shot)
Overall Accuracy· 2023-04-12
81.1
best: 98 (PointGPT)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ClassificationonModelNet40 5-way (10-shot)
Standard Deviation· 2023-04-12
1.5
best: 16 (PointNet++)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ClassificationonModelNet40 10-way (10-shot)
Overall Accuracy· 2023-04-12
71.6
best: 95 (Point-JEPA)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ClassificationonModelNet40 10-way (10-shot)
Standard Deviation· 2023-04-12
1.1
best: 13.5 (PointNet)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ClassificationonModelNet40 5-way (20-shot)
Overall Accuracy· 2023-04-12
82.7
best: 99.5 (ReCon++)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ClassificationonModelNet40 5-way (20-shot)
Standard Deviation· 2023-04-12
1.3
best: 15.5 (PointNet)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ReconstructiononModelNet40 10-way (20-shot)
Overall Accuracy· 2023-04-12
73.8
best: 96.5 (ReCon++)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ReconstructiononModelNet40 10-way (20-shot)
Standard Deviation· 2023-04-12
2
best: 13.5 (PointNet)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ReconstructiononModelNet40 5-way (10-shot)
Overall Accuracy· 2023-04-12
81.1
best: 98 (PointGPT)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ReconstructiononModelNet40 5-way (10-shot)
Standard Deviation· 2023-04-12
1.5
best: 16 (PointNet++)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ReconstructiononModelNet40 10-way (10-shot)
Overall Accuracy· 2023-04-12
71.6
best: 95 (Point-JEPA)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ReconstructiononModelNet40 10-way (10-shot)
Standard Deviation· 2023-04-12
1.1
best: 13.5 (PointNet)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ReconstructiononModelNet40 5-way (20-shot)
Overall Accuracy· 2023-04-12
82.7
best: 99.5 (ReCon++)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007
3D Point Cloud ReconstructiononModelNet40 5-way (20-shot)
Standard Deviation· 2023-04-12
1.3
best: 15.5 (PointNet)
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning arXiv:2304.06007