% Key papers for LiDAR voxel and pillar detectors (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2017_multi_12474,
  title = {{Multi-View 3D Object Detection Network for Autonomous Driving}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{cvpr2020_pointpainting_16046,
  title = {{PointPainting: Sequential Fusion for 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2021_pointaugmenting_17618,
  title = {{PointAugmenting: Cross-Modal Augmentation for 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2022_not_19471,
  title = {{Not All Points Are Equal: Learning Highly Efficient Point-Based Detectors for 3D LiDAR Point Clouds}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2022_embracing_18751,
  title = {{Embracing Single Stride 3D Object Detector With Sparse Transformer}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2020_learning_15748,
  title = {{Learning Depth-Guided Convolutions for Monocular 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2022_sparse_19906,
  title = {{Sparse Fuse Dense: Towards High Quality 3D Detection With Depth Completion}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2021_lidar_17345,
  title = {{LiDAR R-CNN: An Efficient and Universal 3D Object Detector}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2023_spherical_22254,
  title = {{Spherical Transformer for LiDAR-Based 3D Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22665},
}

@inproceedings{cvpr2020_end_15479,
  title = {{End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{neurips2022_bevfusion_66529,
  title = {{BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55002},
}

@inproceedings{aaai2022_behind_1779,
  title = {{Behind the Curtain: Learning Occluded Shapes for 3D Object Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/02893-behind-the-curtain-learning-occluded-shapes-for-3d-object-detection/},
}

@inproceedings{cvpr2023_pillarnext_21869,
  title = {{PillarNeXt: Rethinking Network Designs for 3D Object Detection in LiDAR Point Clouds}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21961},
}

@inproceedings{cvpr2023_logonet_21450,
  title = {{LoGoNet: Towards Accurate 3D Object Detection With Local-to-Global Cross-Modal Fusion}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22710},
}

@inproceedings{cvpr2022_point_19590,
  title = {{Point Density-Aware Voxels for LiDAR 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2022_lidar_19252,
  title = {{LiDAR Snowfall Simulation for Robust 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2020_lidar_15834,
  title = {{LiDAR-Based Online 3D Video Object Detection With Graph-Based Message Passing and Spatiotemporal Transformer Attention}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{neurips2021_multimodal_61485,
  title = {{Multimodal Virtual Point 3D Detection}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28497},
}

@inproceedings{neurips2022_fully_63768,
  title = {{Fully Convolutional One-Stage 3D Object Detection on LiDAR Range Images}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55239},
}

@inproceedings{aaai2023_ssda3d_4586,
  title = {{SSDA3D: Semi-supervised Domain Adaptation for 3D Object Detection from Point Cloud}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25370},
}

@inproceedings{cvpr2024_ptt_24422,
  title = {{PTT: Point-Trajectory Transformer for Efficient Temporal 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29311},
}

@inproceedings{cvpr2025_unimamba_28000,
  title = {{UniMamba: Unified Spatial-Channel Representation Learning with Group-Efficient Mamba for LiDAR-based 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33190},
}

@inproceedings{aaai2024_voxel_7782,
  title = {{Voxel or Pillar: Exploring Efficient Point Cloud Representation for 3D Object Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28018},
}

@inproceedings{aaai2024_idet3d_7849,
  title = {{iDet3D: Towards Efficient Interactive Object Detection for LiDAR Point Clouds}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27897},
}

@inproceedings{cvpr2025_multi_27023,
  title = {{Multi-Scale Neighborhood Occupancy Masked Autoencoder for Self-Supervised Learning in LiDAR Point Clouds}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33312},
}

@inproceedings{aaai2025_a_7911,
  title = {{A New Adversarial Perspective for LiDAR-based 3D Object Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33152},
}

@inproceedings{aaai2025_equirectangular_9007,
  title = {{Equirectangular Point Reconstruction for Domain Adaptive Multimodal 3D Object Detection in Adverse Weather Conditions}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33035},
}

@inproceedings{aaai2025_lion_9788,
  title = {{LiON: Learning Point-Wise Abstaining Penalty for LiDAR Outlier DetectioN Using Diverse Synthetic Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32968},
}

@inproceedings{cvpr2025_gblobs_26348,
  title = {{GBlobs: Explicit Local Structure via Gaussian Blobs for Improved Cross-Domain LiDAR-based 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33232},
}

@inproceedings{cvpr2025_jisam_26667,
  title = {{JiSAM: Alleviate Labeling Burden and Corner Case Problems in Autonomous Driving via Minimal Real-World Data}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35058},
}

@inproceedings{aaai2024_bev_5255,
  title = {{BEV-MAE: Bird’s Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving Scenarios}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28141},
}

@inproceedings{neurips2025_trend_75633,
  title = {{TREND: Unsupervised 3D Representation Learning via Temporal Forecasting for LiDAR Perception}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=AHccBzULR7},
}

@inproceedings{aaai2026_physically_105592,
  title = {{Physically-Based LiDAR Smoke Simulation for Robust 3D Object Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38348},
}

@inproceedings{aaai2025_beyond_8258,
  title = {{Beyond Virtual Points: Depth-Enhanced LiDAR-only 3D Object Detection with Semi-Supervised Learning (Student Abstract)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35264},
}

@inproceedings{iclr2024_pre_34879,
  title = {{Pre-training LiDAR-based 3D Object Detectors through Colorization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18195},
}

@inproceedings{neurips2024_stone_71198,
  title = {{STONE: A Submodular Optimization Framework for Active 3D Object Detection}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96033},
}

@inproceedings{neurips2024_just_71890,
  title = {{Just Add \$100 More: Augmenting Pseudo-LiDAR Point Cloud for Resolving Class-imbalance Problem}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95413},
}

@inproceedings{cvpr2026_ghost_99564,
  title = {{Ghost-FWL: A Large-Scale Full-Waveform LiDAR Dataset for Ghost Detection and Removal}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Ikeda_Ghost-FWL_A_Large-Scale_Full-Waveform_LiDAR_Dataset_for_Ghost_Detection_and_CVPR_2026_paper.html},
}

@inproceedings{aaai2026_weather_104346,
  title = {{Weather-Robust LiDAR Perception: Point Cloud Restoration from Adverse Weather}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37873},
}

@inproceedings{aaai2026_temporal_104656,
  title = {{Temporal and Spatial Representation Learning for Multimodal Low-Beam 3D Object Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37960},
}