% Key papers for Local feature aggregation networks (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2017_pointnet_12538,
  title = {{PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{neurips2017_pointnet_56573,
  title = {{PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9286},
}

@inproceedings{cvpr2019_pointconv_14650,
  title = {{PointConv: Deep Convolutional Networks on 3D Point Clouds}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2017_octnet_12503,
  title = {{OctNet: Learning Deep 3D Representations at High Resolutions}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2019_relation_14725,
  title = {{Relation-Shape Convolutional Neural Network for Point Cloud Analysis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2018_so_13553,
  title = {{SO-Net: Self-Organizing Network for Point Cloud Analysis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Li_SO-Net_Self-Organizing_Network_CVPR_2018_paper.html},
}

@inproceedings{cvpr2019_pointweb_14655,
  title = {{PointWeb: Enhancing Local Neighborhood Features for Point Cloud Processing}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2018_splatnet_13554,
  title = {{SPLATNet: Sparse Lattice Networks for Point Cloud Processing}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Su_SPLATNet_Sparse_Lattice_CVPR_2018_paper.html},
}

@inproceedings{cvpr2018_pointnetvlad_13477,
  title = {{PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Uy_PointNetVLAD_Deep_Point_CVPR_2018_paper.html},
}

@inproceedings{cvpr2020_pointasnl_16042,
  title = {{PointASNL: Robust Point Clouds Processing Using Nonlocal Neural Networks With Adaptive Sampling}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2018_ppfnet_13452,
  title = {{PPFNet: Global Context Aware Local Features for Robust 3D Point Matching}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Deng_PPFNet_Global_Context_CVPR_2018_paper.html},
}

@inproceedings{cvpr2024_point_24480,
  title = {{Point Transformer V3: Simpler Faster Stronger}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29650},
}

@inproceedings{cvpr2018_mining_13371,
  title = {{Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Shen_Mining_Point_Cloud_CVPR_2018_paper.html},
}

@inproceedings{cvpr2022_stratified_19938,
  title = {{Stratified Transformer for 3D Point Cloud Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2019_the_14911,
  title = {{The Perfect Match: 3D Point Cloud Matching With Smoothed Densities}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2018_recurrent_13515,
  title = {{Recurrent Slice Networks for 3D Segmentation of Point Clouds}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Huang_Recurrent_Slice_Networks_CVPR_2018_paper.html},
}

@inproceedings{cvpr2021_paconv_17554,
  title = {{PAConv: Position Adaptive Convolution With Dynamic Kernel Assembling on Point Clouds}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2018_pointgrid_13476,
  title = {{PointGrid: A Deep Network for 3D Shape Understanding}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Le_PointGrid_A_Deep_CVPR_2018_paper.html},
}

@inproceedings{cvpr2018_attentional_12850,
  title = {{Attentional ShapeContextNet for Point Cloud Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Xie_Attentional_ShapeContextNet_for_CVPR_2018_paper.html},
}

@inproceedings{aaai2019_point2sequence_103505,
  title = {{Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-Based Sequence to Sequence Network}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4903},
}

@inproceedings{cvpr2024_kpconvx_23861,
  title = {{KPConvX: Modernizing Kernel Point Convolution with Kernel Attention}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30275},
}

@inproceedings{cvpr2024_denoising_23143,
  title = {{Denoising Point Clouds in Latent Space via Graph Convolution and Invertible Neural Network}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31193},
}

@inproceedings{aaai2024_interpretable3d_6346,
  title = {{Interpretable3D: An Ad-Hoc Interpretable Classifier for 3D Point Clouds}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27944},
}

@inproceedings{cvpr2024_x_25292,
  title = {{X-3D: Explicit 3D Structure Modeling for Point Cloud Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31453},
}

@inproceedings{cvpr2024_pbwr_24397,
  title = {{PBWR: Parametric-Building-Wireframe Reconstruction from Aerial LiDAR Point Clouds}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29867},
}

@inproceedings{aaai2024_dhgcn_5561,
  title = {{DHGCN: Dynamic Hop Graph Convolution Network for Self-Supervised Point Cloud Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29185},
}

@inproceedings{cvpr2025_lidargait_26789,
  title = {{LidarGait++: Learning Local Features and Size Awareness from LiDAR Point Clouds for 3D Gait Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33502},
}

@inproceedings{aaai2024_point_6959,
  title = {{Point Deformable Network with Enhanced Normal Embedding for Point Cloud Analysis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28497},
}

@inproceedings{cvpr2024_tetrasphere_24977,
  title = {{TetraSphere: A Neural Descriptor for O(3)-Invariant Point Cloud Analysis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30019},
}

@inproceedings{aaai2024_compact_5436,
  title = {{Compact HD Map Construction via Douglas-Peucker Point Transformer}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28160},
}

@inproceedings{aaai2024_complete_5440,
  title = {{Complete Neural Networks for Complete Euclidean Graphs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29141},
}

@inproceedings{cvpr2025_deepla_25885,
  title = {{DeepLA-Net: Very Deep Local Aggregation Networks for Point Cloud Analysis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32644},
}

@inproceedings{cvpr2025_star_27546,
  title = {{STAR-Edge: Structure-aware Local Spherical Curve Representation for Thin-walled Edge Extraction from Unstructured Point Clouds}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35053},
}

@inproceedings{cvpr2024_curvecloudnet_23069,
  title = {{CurveCloudNet: Processing Point Clouds with 1D Structure}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30895},
}

@inproceedings{cvpr2025_mitigating_26963,
  title = {{Mitigating Ambiguities in 3D Classification with Gaussian Splatting}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33206},
}

@inproceedings{neurips2024_linnet_73180,
  title = {{LinNet: Linear Network for Efficient Point Cloud Representation Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94253},
}

@inproceedings{neurips2024_rethinking_73584,
  title = {{Rethinking 3D Convolution in \$ell\_p\$-norm Space}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93901},
}

@inproceedings{aaai2026_hierarchical_100743,
  title = {{Hierarchical Direction Perception via Atomic Dot-Product Operators for Rotation-Invariant Point Clouds Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/42483},
}

@inproceedings{aaai2026_cloudmamba_104291,
  title = {{CloudMamba: Grouped Selective State Spaces for Point Cloud Analysis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37818},
}