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

@inproceedings{cvpr2021_cylindrical_16780,
  title = {{Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2020_polarnet_16049,
  title = {{PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{aaai2021_sparse_1405,
  title = {{Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/03101-sparse-single-sweep-lidar-point-cloud-segmentation-via-learning-contextual-shape-priors-from-scene-completion/},
}

@inproceedings{cvpr2022_point_19594,
  title = {{Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2021_complete_16729,
  title = {{Complete \& Label: A Domain Adaptation Approach to Semantic Segmentation of LiDAR Point Clouds}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2023_rangevit_21979,
  title = {{RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21667},
}

@inproceedings{cvpr2021_panoptic_17575,
  title = {{Panoptic-PolarNet: Proposal-Free LiDAR Point Cloud Panoptic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2023_mseg3d_21506,
  title = {{MSeg3D: Multi-Modal 3D Semantic Segmentation for Autonomous Driving}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22924},
}

@inproceedings{aaai2022_transfer_2882,
  title = {{Transfer Learning from Synthetic to Real LiDAR Point Cloud for Semantic Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/02795-transfer-learning-from-synthetic-to-real-lidar-point-cloud-for-semantic-segmentation/},
}

@inproceedings{cvpr2022_image_19053,
  title = {{Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2023_lasermix_21326,
  title = {{LaserMix for Semi-Supervised LiDAR Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22996},
}

@inproceedings{aaai2021_epointda_1649,
  title = {{ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/03500-epointda-an-end-to-end-simulation-to-real-domain-adaptation-framework-for-lidar-point-cloud-segmentation/},
}

@inproceedings{cvpr2022_scribble_19807,
  title = {{Scribble-Supervised LiDAR Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2021_lidar_17347,
  title = {{LiDAR-Based Panoptic Segmentation via Dynamic Shifting Network}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2021_4d_16527,
  title = {{4D Panoptic LiDAR Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{aaai2024_nerf_6748,
  title = {{NeRF-LiDAR: Generating Realistic LiDAR Point Clouds with Neural Radiance Fields}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28546},
}

@inproceedings{cvpr2023_less_21430,
  title = {{Less Is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/23130},
}

@inproceedings{neurips2022_polarmix_66354,
  title = {{PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55374},
}

@inproceedings{aaai2024_vlm2scene_7744,
  title = {{VLM2Scene: Self-Supervised Image-Text-LiDAR Learning with Foundation Models for Autonomous Driving Scene Understanding}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28121},
}

@inproceedings{cvpr2022_be_18333,
  title = {{BE-STI: Spatial-Temporal Integrated Network for Class-Agnostic Motion Prediction With Bidirectional Enhancement}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2024_taseg_24936,
  title = {{TASeg: Temporal Aggregation Network for LiDAR Semantic Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29735},
}

@inproceedings{cvpr2024_lisa_24006,
  title = {{LiSA: LiDAR Localization with Semantic Awareness}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30427},
}

@inproceedings{cvpr2025_limoe_26784,
  title = {{LiMoE: Mixture of LiDAR Representation Learners from Automotive Scenes}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34689},
}

@inproceedings{cvpr2025_hilots_26503,
  title = {{HiLoTs: High-Low Temporal Sensitive Representation Learning for Semi-Supervised LiDAR Segmentation in Autonomous Driving}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33588},
}

@inproceedings{cvpr2024_construct_23020,
  title = {{Construct to Associate: Cooperative Context Learning for Domain Adaptive Point Cloud Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30078},
}

@inproceedings{cvpr2025_towards_27902,
  title = {{Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33301},
}

@inproceedings{cvpr2025_psa_27204,
  title = {{PSA-SSL: Pose and Size-aware Self-Supervised Learning on LiDAR Point Clouds}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34379},
}

@inproceedings{aaai2025_3d_7864,
  title = {{3D Annotation-Free Learning by Distilling 2D Open-Vocabulary Segmentation Models for Autonomous Driving}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32760},
}

@inproceedings{cvpr2025_3d_25333,
  title = {{3D-AVS: LiDAR-based 3D Auto-Vocabulary Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33831},
}

@inproceedings{cvpr2025_d_25852,
  title = {{D^3CTTA: Domain-Dependent Decorrelation for Continual Test-Time Adaption of 3D LiDAR Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33594},
}

@inproceedings{neurips2024_spherical_71719,
  title = {{Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95567},
}

@inproceedings{iclr2026_adaptive_88283,
  title = {{Adaptive Augmentation-Aware Latent Learning for Robust LiDAR Semantic Segmentation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=l7Cwq08AO0},
}

@inproceedings{cvpr2026_terraseg_96232,
  title = {{TerraSeg: Self-Supervised Ground Segmentation for Any LiDAR}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Lentsch_TerraSeg_Self-Supervised_Ground_Segmentation_for_Any_LiDAR_CVPR_2026_paper.html},
}

@inproceedings{cvpr2026_learning_96463,
  title = {{Learning to Identify Out-of-Distribution Objects for 3D LiDAR Anomaly Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Mosco_Learning_to_Identify_Out-of-Distribution_Objects_for_3D_LiDAR_Anomaly_Segmentation_CVPR_2026_paper.html},
}

@inproceedings{aaai2026_beyondsparse_104869,
  title = {{BeyondSparse: Facilitating Mamba to Enhance Cross-Domain 3D Semantic Segmentation in Adverse Weather}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38058},
}

@inproceedings{aaai2026_xmhashseg_105492,
  title = {{xMHashSeg: Cross-modal Hash Learning for Training-free Unsupervised LiDAR Semantic Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38248},
}

@inproceedings{neurips2025_beyondmix_80416,
  title = {{BeyondMix: Leveraging Structural Priors and Long-Range Dependencies for Domain-Invariant LiDAR Segmentation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=zKV3CN40tE},
}

@inproceedings{cvpr2026_srgcd_95737,
  title = {{SRGCD: Stability-Driven Region Growth Framework for 3D Change Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Wu_SRGCD_Stability-Driven_Region_Growth_Framework_for_3D_Change_Detection_CVPR_2026_paper.html},
}