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SOTA
세마틱 세그멘테이션
Semantic Segmentation On S3Dis
Semantic Segmentation On S3Dis
평가 지표
Mean IoU
Number of params
oAcc
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
Mean IoU
Number of params
oAcc
Paper Title
Sonata + PTv3
82.3
128M
93.3
Sonata: Self-Supervised Learning of Reliable Point Representations
PTv3 + PPT
80.8
24.1M
92.6
Point Transformer V3: Simpler, Faster, Stronger
PonderV2 + SparseUNet
79.9
-
92.5
PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm
Swin3D-L
79.8
N/A
92.4
Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding
PointVector-XL
78.4
-
91.9
PointVector: A Vector Representation In Point Cloud Analysis
PPT + SparseUNet
78.1
N/A
92.2
Towards Large-scale 3D Representation Learning with Multi-dataset Point Prompt Training
WindowNorm+StratifiedTransformer
77.6
8.2M
91.7
Window Normalization: Enhancing Point Cloud Understanding by Unifying Inconsistent Point Densities
EQ-Net
77.5
N/A
-
A Unified Query-based Paradigm for Point Cloud Understanding
PointMetaBase-XXL
77.0
19.7M
91.3
Meta Architecture for Point Cloud Analysis
Superpoint Transformer
76.0
0.212M
90.4
Efficient 3D Semantic Segmentation with Superpoint Transformer
SuperCluster
75.3
0.21M
-
Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering
PointNeXt-XL
74.9
41.6M
90.3
PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
DeepViewAgg
74.7
41.2M
90.1
Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation
RepSurf-U
74.3
0.97M
90.8
Surface Representation for Point Clouds
WindowNorm+PointTransformer
74.1
8.0M
90.2
Window Normalization: Enhancing Point Cloud Understanding by Unifying Inconsistent Point Densities
PointNeXt-L
73.9
7.1M
89.9
PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
PointTransformer
73.5
7.8M
90.2
Point Transformer
CBL
73.1
N/A
89.6
Contrastive Boundary Learning for Point Cloud Segmentation
BAAF-Net
72.2
N/A
88.9
Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion
SCF-Net
71.6
N/A
88.4
SCF-Net: Learning Spatial Contextual Features for Large-Scale Point Cloud Segmentation
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