| Exploiting Local Geometry for Feature and Graph Construction for Better 3D Point Cloud Processing with Graph Neural Networks | | 89.1 | | GeomGCNN | 2021-03-28 |
| Beyond local patches: Preserving global–local interactions by enhancing self-attention via 3D point cloud tokenization | | 88.1 | | Ours | 2024-11-01 |
| AVS-Net: Point Sampling with Adaptive Voxel Size for 3D Scene Understanding | ✓ Link | 87.3 | 85.7 | AVS-Net | 2024-02-27 |
| Self-positioning Point-based Transformer for Point Cloud Understanding | ✓ Link | 87.2 | 85.4 | SPoTr | 2023-03-29 |
| PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies | ✓ Link | 87.1 | 85.2 | PointNeXt | 2022-06-09 |
| Diffusion Unit: Interpretable Edge Enhancement and Suppression Learning for 3D Point Cloud Segmentation | ✓ Link | 87.1 | 85.2 | Diffusion Unit | 2022-09-20 |
| $(0, 4)$ dualities | | 87.0 | | CurveNet+GAM | 2015-12-14 |
| DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds | ✓ Link | 86.9 | | DeltaConv (U-ResNet) | 2021-11-16 |
| AGCN: Adversarial Graph Convolutional Network for 3D Point Cloud Segmentation | ✓ Link | 86.9 | 85.7 | AGCN | 2021-11-25 |
| PointVector: A Vector Representation In Point Cloud Analysis | ✓ Link | 86.9 | | PointVector-S(C=64) | 2022-05-21 |
| Take-A-Photo: 3D-to-2D Generative Pre-training of Point Cloud Models | ✓ Link | 86.9 | 85.2 | PointMLP+TAP | 2023-07-27 |
| Octree guided CNN with Spherical Kernels for 3D Point Clouds | | 86.8 | 83.4 | Ps-CNN | 2019-02-28 |
| Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds | ✓ Link | 86.8 | 84.9 | Spherical Kernel | 2019-09-20 |
| Walk in the Cloud: Learning Curves for Point Clouds Shape Analysis | ✓ Link | 86.8 | | CurveNet | 2021-05-04 |
| Rethinking Masked Representation Learning for 3D Point Cloud Understanding | ✓ Link | 86.8 | 85.1 | OTMae3D | 2024-12-26 |
| MKConv: Multidimensional Feature Representation for Point Cloud Analysis | | 86.7 | | MKConv | 2021-07-27 |
| Point Transformer | ✓ Link | 86.6 | 83.7 | PointTransformer | 2020-12-16 |
| FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware Modelling | ✓ Link | 86.6 | 87.7 | Feature Geometric Net (FG-Net) | 2020-12-17 |
| []() | | 86.6 | 84.8 | PointGPT | |
| DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds | ✓ Link | 86.6 | | DeltaNet | 2021-11-16 |
| ODFNet: Using orientation distribution functions to characterize 3D point clouds | ✓ Link | 86.5 | 83.3 | ODFNet | 2020-12-08 |
| Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud | ✓ Link | 86.5 | 85.0 | GDANet | 2020-12-20 |
| PVT: Point-Voxel Transformer for Point Cloud Learning | ✓ Link | 86.5 | | Point Voxel Transformer | 2021-08-13 |
| P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting | ✓ Link | 86.5 | | P2P | 2022-08-04 |
| PointGrid: A Deep Network for 3D Shape Understanding | ✓ Link | 86.4 | 82.2 | PointGrid | 2018-06-01 |
| KPConv: Flexible and Deformable Convolution for Point Clouds | ✓ Link | 86.4 | 85.1 | KPConv | 2019-04-18 |
| DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing | ✓ Link | 86.4 | 84.2 | DensePoint | 2019-09-09 |
| Dense-Resolution Network for Point Cloud Classification and Segmentation | ✓ Link | 86.4 | 83.7 | DRNet | 2020-05-14 |
| PCT: Point cloud transformer | ✓ Link | 86.4 | | Point Cloud Transformer | 2020-12-17 |
| Interpolated Convolutional Networks for 3D Point Cloud Understanding | | 86.3 | 84.0 | InterpCNN | 2019-08-13 |
| Point2Vec for Self-Supervised Representation Learning on Point Clouds | ✓ Link | 86.3 | 84.6 | point2vec | 2023-03-29 |
| Relation-Shape Convolutional Neural Network for Point Cloud Analysis | ✓ Link | 86.2 | | RS-CNN | 2019-04-16 |
| Point-Voxel CNN for Efficient 3D Deep Learning | ✓ Link | 86.2 | | PVCNN volumetric | 2019-07-08 |
| Exploiting Inductive Bias in Transformer for Point Cloud Classification and Segmentation | ✓ Link | 86.2 | | Ours | 2023-04-27 |
| PointCNN: Convolution On $\mathcal{X}$-Transformed Points | ✓ Link | 86.14 | 84.6 | PointCNN | 2018-01-23 |
| ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning | ✓ Link | 86.1 | | ASSANet | 2021-10-20 |
| Submanifold Sparse Convolutional Networks | ✓ Link | 86.0 | | SSCN | 2017-06-05 |
| Point Transformer | ✓ Link | 85.9 | | Point Transformer | 2020-11-02 |
| SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation | ✓ Link | 85.8 | | SGPN | 2017-11-23 |
| ConvPoint: Continuous Convolutions for Point Cloud Processing | ✓ Link | 85.8 | 83.4 | ConvPoint | 2019-04-04 |
| DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion | ✓ Link | 85.8 | 83.9 | DSPoint | 2021-11-19 |
| Attention-based Point Cloud Edge Sampling | ✓ Link | 85.8 | 83.7 | APES (global_based downsample) | 2023-02-28 |
| PointConv: Deep Convolutional Networks on 3D Point Clouds | ✓ Link | 85.7 | 82.8 | PointConv | 2018-11-17 |
| SageMix: Saliency-Guided Mixup for Point Clouds | ✓ Link | 85.7 | | PointNet++ + SageMix | 2022-10-13 |
| Attention-based Point Cloud Edge Sampling | ✓ Link | 85.6 | 83.1 | APES (local_based downsample) | 2023-02-28 |
| Self-supervised Point Cloud Representation Learning via Separating Mixed Shapes | ✓ Link | 85.5 | | DGCNN + MD | 2021-09-01 |
| Spherical Fractal Convolutional Neural Networks for Point Cloud Recognition | | 85.4 | 82.7 | SFCNN | 2019-06-01 |
| SageMix: Saliency-Guided Mixup for Point Clouds | ✓ Link | 85.4 | | DGCNN + SageMix | 2022-10-13 |
| SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters | ✓ Link | 85.3 | 82.4 | SpiderCNN | 2018-03-30 |
| Structural Relational Reasoning of Point Clouds | | 85.3 | 82.2 | SRN | 2019-06-01 |
| Dynamic Graph CNN for Learning on Point Clouds | ✓ Link | 85.2 | | DGCNN | 2018-01-24 |
| Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-based Sequence to Sequence Network | | 85.2 | | P2Sequence | 2018-11-06 |
| PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space | ✓ Link | 85.1 | 81.9 | PointNet++ | 2017-06-07 |
| Point-PlaneNet: Plane kernel based convolutional neural network for point clouds analysis | ✓ Link | 85.1 | 82.5 | Point-PlaneNet | 2020-05-01 |
| Convolution in the Cloud: Learning Deformable Kernels in 3D Graph Convolution Networks for Point Cloud Analysis | ✓ Link | 85.1 | 82.1 | 3D-GCN | 2020-06-01 |
| 3D-JEPA: A Joint Embedding Predictive Architecture for 3D Self-Supervised Representation Learning | | 84.93 | 86.41 | 3D-JEPA | 2024-09-24 |
| SO-Net: Self-Organizing Network for Point Cloud Analysis | ✓ Link | 84.9 | | SO-Net | 2018-03-12 |
| SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation | | 84.7 | 82.0 | SSCNN | 2016-12-02 |
| 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation | ✓ Link | 84.6 | | 3D-UNet [Cicek:2016un] | 2016-06-21 |
| SPLATNet: Sparse Lattice Networks for Point Cloud Processing | ✓ Link | 84.6 | 82.0 | SPLATNet 3D | 2018-02-22 |
| 3D Point Cloud Classification and Segmentation using 3D Modified Fisher Vector Representation for Convolutional Neural Networks | ✓ Link | 84.3 | | 3DmFV-Net | 2017-11-22 |
| Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud | ✓ Link | 83.9 | 85.8 | Point-JEPA | 2024-04-25 |
| PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation | ✓ Link | 83.7 | | PointNet | 2016-12-02 |
| Escape from Cells: Deep Kd-Networks for the Recognition of 3D Point Cloud Models | ✓ Link | 82.3 | 77.4 | Kd-net | 2017-04-04 |
| AdaCrossNet: Adaptive Dynamic Loss Weighting for Cross-Modal Contrastive Point Cloud Learning | ✓ Link | | 85.1 | AdaCrossNet | 2025-01-02 |
| PartNet: A Recursive Part Decomposition Network for Fine-grained and Hierarchical Shape Segmentation | | | 84.1 | PartNet | 2019-03-02 |
| Beyond First Impressions: Integrating Joint Multi-modal Cues for Comprehensive 3D Representation | ✓ Link | | 82.1 | PointNet++ (ssg) + JM3D | 2023-08-06 |