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Models/RPNet

RPNet

Reported on 16 benchmarks across 8 tasks · 1 paper

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 CloudsonModelNet40
Overall Accuracy· 2021-08-27
94.1
best: 95.3 (PointGST)
Learning Inner-Group Relations on Point Clouds arXiv:2108.12468
3D Point Cloud ClassificationonModelNet40
Overall Accuracy· 2021-08-27
94.1
best: 95.3 (PointGST)
Learning Inner-Group Relations on Point Clouds arXiv:2108.12468
3D Point Cloud ReconstructiononModelNet40
Overall Accuracy· 2021-08-27
94.1
best: 95.3 (PointGST)
Learning Inner-Group Relations on Point Clouds arXiv:2108.12468
HyperspectralonPavia University
OA@15perclass
84.92
best: 95.6 (RPNet-RF)
HyperspectralonKennedy Space Center
OA@15perclass
95.83
best: 98.51 (RPNet-RF)
HyperspectralonIndian Pines
OA@15perclass
77.97
best: 92.37 (HyperspectralMAE)
Image ClassificationonPavia University
OA@15perclass
84.92
best: 95.6 (RPNet-RF)
Image ClassificationonKennedy Space Center
OA@15perclass
95.83
best: 98.51 (RPNet-RF)
Image ClassificationonIndian Pines
OA@15perclass
77.97
best: 92.37 (HyperspectralMAE)
Hyperspectral Image SegmentationonPavia University
OA@15perclass
84.92
best: 95.6 (RPNet-RF)
Hyperspectral Image SegmentationonKennedy Space Center
OA@15perclass
95.83
best: 98.51 (RPNet-RF)
Hyperspectral Image SegmentationonIndian Pines
OA@15perclass
77.97
best: 92.37 (HyperspectralMAE)

Medical2 results

Semantic SegmentationonScanNet
test mIoU· 2021-08-27
68.2
best: 79.8 (PTv3 ARKit LabelMaker)
Learning Inner-Group Relations on Point Clouds arXiv:2108.12468
Semantic SegmentationonS3DIS
Mean IoU· 2021-08-27
70.8
best: 82.3 (Sonata + PTv3)
Learning Inner-Group Relations on Point Clouds arXiv:2108.12468

Audio2 results

10-shot image generationonScanNet
test mIoU· 2021-08-27
68.2
best: 79.8 (PTv3 ARKit LabelMaker)
Learning Inner-Group Relations on Point Clouds arXiv:2108.12468
10-shot image generationonS3DIS
Mean IoU· 2021-08-27
70.8
best: 82.3 (Sonata + PTv3)
Learning Inner-Group Relations on Point Clouds arXiv:2108.12468