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Models/SSCNN

SSCNN

Reported on 6 benchmarks across 3 tasks · 2 papers · 6 SOTA

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

Medical2 results

Semantic SegmentationonShapeNet-Part
Class Average IoU· 2016-12-02
82
best: 87.7 (Feature Geometric Net (FG-Net))
SOTA
SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation arXiv:1612.00606
Semantic SegmentationonShapeNet-Part
Instance Average IoU· 2016-12-02
84.7
best: 89.1 (GeomGCNN)
SOTA
SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation arXiv:1612.00606

Audio2 results

10-shot image generationonShapeNet-Part
Class Average IoU· 2016-12-02
82
best: 87.7 (Feature Geometric Net (FG-Net))
SOTA
SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation arXiv:1612.00606
10-shot image generationonShapeNet-Part
Instance Average IoU· 2016-12-02
84.7
best: 89.1 (GeomGCNN)
SOTA
SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation arXiv:1612.00606

Computer Vision2 results

Image ClassificationonCIFAR-10
Percentage correct· 2014-09-22
93.7
best: 99.5 (ViT-H/14)
SOTA
Spatially-sparse convolutional neural networks arXiv:1409.6070
Image ClassificationonCIFAR-100
Percentage correct· uses extra data· 2014-09-22
75.7
best: 96.08 (EffNet-L2 (SAM))
SOTA
Spatially-sparse convolutional neural networks arXiv:1409.6070