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SotA/Computer Vision/3D Point Cloud Classification/ScanObjectNN

3D Point Cloud Classification on ScanObjectNN

Metric: Number of params (M) (higher is better)

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#Model↕Number of params (M)▼Extra DataPaperDate↕Code
1PCM34.2NoPoint Cloud Mamba: Point Cloud Learning via Stat...2024-03-01Code
2Transformer22.1NoAttention Is All You Need2017-06-12Code
3Mamba3D16.9NoMamba3D: Enhancing Local Features for 3D Point C...2024-04-23Code
4Mamba3D (no voting)16.9NoMamba3D: Enhancing Local Features for 3D Point C...2024-04-23Code
5PointMLP12.6NoRethinking Network Design and Local Geometry in ...2022-02-15Code
6DeLA5.3NoDecoupled Local Aggregation for Point Cloud Lear...2023-08-31Code
7PointNet3.5NoPointNet: Deep Learning on Point Sets for 3D Cla...2016-12-02Code
8DGCNN1.8NoDynamic Graph CNN for Learning on Point Clouds2018-01-24Code
9SPoTr1.7NoSelf-positioning Point-based Transformer for Poi...2023-03-29Code
10PointNet++1.5NoPointNet++: Deep Hierarchical Feature Learning o...2017-06-07Code
11PointNeXt1.4NoPointNeXt: Revisiting PointNet++ with Improved T...2022-06-09Code
12Point-PN0.8NoParameter is Not All You Need: Starting from Non...2023-03-14Code