3D Part Segmentation On Intra

Métriques

DSC (A)

DSC (V)

IoU (A)

IoU (V)

Résultats

Résultats de performance de divers modèles sur ce benchmark

					Paper Title
3DMedPT	89.71	97.29	82.39	94.82	3D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysis
SO-Net	88.76	97.09	81.40	94.46	SO-Net: Self-Organizing Network for Point Cloud Analysis
PointConv	86.52	97.18	79.53	94.65	PointConv: Deep Convolutional Networks on 3D Point Clouds
PointNet++	84.64	96.48	76.38	93.42	PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
PointCNN	81.74	96.62	74.11	93.59	PointCNN: Convolution On $\mathcal{X}$-Transformed Points
SpiderCNN	75.82	94.53	67.25	90.16	SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters
PointNet	49.59	85.00	37.75	75.23	PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

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3D Part Segmentation On Intra | SOTA | HyperAI