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K
홈
SOTA
3D 부품 분할
3D Part Segmentation On Shapenet Part
3D Part Segmentation On Shapenet Part
평가 지표
Class Average IoU
Instance Average IoU
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
Class Average IoU
Instance Average IoU
Paper Title
Repository
InterpCNN
84.0
86.3
Interpolated Convolutional Networks for 3D Point Cloud Understanding
-
Point Voxel Transformer
-
86.5
PVT: Point-Voxel Transformer for Point Cloud Learning
Point-JEPA
85.8±0.1
-
Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud
-
SSCNN
82.0
84.7
SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation
-
Point Cloud Transformer
-
86.4
PCT: Point cloud transformer
DensePoint
84.2
86.4
DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing
CurveNet
-
86.8
Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis
3D-JEPA
86.41
84.93
3D-JEPA: A Joint Embedding Predictive Architecture for 3D Self-Supervised Representation Learning
-
KPConv
85.1
86.4
KPConv: Flexible and Deformable Convolution for Point Clouds
GeomGCNN
-
89.1
Exploiting Local Geometry for Feature and Graph Construction for Better 3D Point Cloud Processing with Graph Neural Networks
-
PartNet
84.1
-
PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation
-
point2vec
84.6
86.3
Point2Vec for Self-Supervised Representation Learning on Point Clouds
RS-CNN
-
86.2
Relation-Shape Convolutional Neural Network for Point Cloud Analysis
SGPN
-
85.8
SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation
P2Sequence
-
85.2
Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-based Sequence to Sequence Network
-
PointNet
-
83.7
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointGPT
84.8
86.6
-
-
PointGrid
82.2
86.4
PointGrid: A Deep Network for 3D Shape Understanding
DeltaConv (U-ResNet)
-
86.9
DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds
ConvPoint
83.4
85.8
ConvPoint: Continuous Convolutions for Point Cloud Processing
0 of 67 row(s) selected.
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