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3D-Point-Cloud

1.PointNet (CVPR-2017) (Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition)
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
2.PointNet++ (NIPS-2017)
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
3.PointASNL (CVPR-2020)
PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling
4.APES (CVPR-2023)
Attention-Based Point Cloud Edge Sampling [Code]

5.PointMLP (ICLR-2022)
Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework

6.PointGS (Inf Fusion-2023)
PointGS: Bridging and Fusing Geometric and Semantic Space for 3D Point Cloud Analysis

7.PointWavelet (TNNLS-2024)
PointWavelet: Learning in Spectral Domain for 3D Point Cloud Analysis

8.DGCNN (TOG-2019) (ACM Transactions on Graphics)
Dynamic Graph CNN for Learning on Point Clouds [Code]
9.LDGCNN (M2VIP-2021) (International Conference on Mechatronics and Machine Vision in Practice)
Linked Dynamic Graph CNN: Learning on Point Cloud via Linking Hierarchical Features [Code]
10.GeomGCNN (ICRA-2021) (IEEE International Conference on Robotics and Automation)
Exploiting Local Geometry for Feature and Graph Construction for Better 3D Point Cloud Processing with Graph Neural Networks
11.DC-GNN (IJMIR-2022) (International Journal of Multimedia Information Retrieval)
DC-GNN: Drop Channel Graph Neural Network for Object Classification and Part Segmentation in the Point Cloud [Code]
12.DGACN (TNNLS-2022) (IEEE Transactions on Neural Networks and Learning Systems)
Dual-Graph Attention Convolution Network for 3-D Point Cloud Classification
13.DiffConv (ECCV-2022) (European Conference on Computer Vision)
DiffConv: Analyzing Irregular Point Clouds with an Irregular View [Code]
14.LGPA (IEEE Access-2023)
Local Graph Point Attention Network in Point Cloud Segmentation

15.DeepGCNs (ICCV-2019) (Proceedings of the IEEE/CVF International Conference on Computer Vision)
DeepGCNs: Can GCNs Go as Deep as CNNs? [Code]
16.GACNet (CVPR-2019)
Graph Attention Convolution for Point Cloud Semantic Segmentation [Code]
17.FGCN (CVPR-2020)
FGCN: Deep Feature-based Graph Convolutional Network for Semantic Segmentation of Urban 3D Point Clouds
18.GAPointNet (Neurocomputing-2021)
GAPointNet: Graph Attention Based Point Neural Network for Exploiting Local Feature of Point Cloud
19.MLGCN (2023)
MLGCN: An Ultra Efficient Graph Convolution Neural Model For 3D Point Cloud Analysis
20.GSLCN (TPAMI-2023)
Long and Short-Range Dependency Graph Structure Learning Framework on Point Cloud

21.3D-GCN (TPAMI-2021) (IEEE Transactions on Pattern Analysis and Machine Intelligence)
Learning of 3D Graph Convolution Networks for Point Cloud Analysis

22.KPConv (ICCV-2019)
KPConv: Flexible and Deformable Convolution for Point Clouds [Code]
23.PAConv (CVPR-2021)
PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds [Code]
24.AGConv (TPAMI-2023)
AGConv: Adaptive Graph Convolution on 3D Point Clouds [Code]
25.SAKS (TCSVT-2023)
SAKS: Sampling Adaptive Kernels from Subspace for Point Cloud Graph Convolution

26.PCT (CVM-2021)
PCT: Point Cloud Transformer
27.Point Transformer (ICCV-2021)
Point Transformer
28.Point Transformer (IEEE Access-2021)
Point Transformer
29.Stratified Transformer (CVPR-2022)
Stratified Transformer for 3D Point Cloud Segmentation
30.AGNet (Remote Sensing-2022)
AGNet: An Attention-Based Graph Network for Point Cloud Classification and Segmentation
31.3DCTN (TITS-2022) (IEEE Transactions on Intelligent Transportation Systems)
3DCTN: 3D Convolution-Transformer Network for Point Cloud Classification [Code]
32.SPoTr (CVPR-2023)
Self-positioning Point-based Transformer for Point Cloud Understanding
33.GTNet (2023)
GTNet: Graph Transformer Network for 3D Point Cloud Classification and Semantic Segmentation
34.AF-GCN (CVPR-2023)
Improving Graph Representation for Point Cloud Segmentation via Attentive Filtering
35.PointCT (WACV-2024)
PointCT: Point Central Transformer Network for Weakly-supervised Point Cloud Semantic Segmentation
36.3DGTN (TGRS-2024) (IEEE Transactions on Geoscience and Remote Sensing)
3DGTN: 3-D Dual-Attention GLocal Transformer Network for Point Cloud Classification and Segmentation [Code]
37.PointNAT (TGRS-2024)
PointNAT: Large-Scale Point Cloud Semantic Segmentation via Neighbor Aggregation With Transformer [Code]

38.CP-Net (CVPR-2020)
Adaptive Hierarchical Down-Sampling for Point Cloud Classification
39.GBNet (TMM-2021) (IEEE Transactions on Multimedia)
Geometric Back-projection Network for Point Cloud Classification [Code]
40.(ICCV-2021)
Towards Efficient Point Cloud Graph Neural Networks Through Architectural Simplification
41.BubblEX (JSTARS-2022) (IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing)
BubblEX: An Explainable Deep Learning Framework for Point-Cloud Classification [Code]
42.GrowSP (CVPR-2023)
GrowSP: Unsupervised Semantic Segmentation of 3D Point Clouds [Code]

43.A Survey (TPAMI-2020)
Deep Learning for 3D Point Clouds: A Survey
44.A Systematic Survey and Outlook (Displays-2023)
Deep Learning-based 3D Point Cloud Classification: A Systematic Survey and Outlook