% Key papers for Depth-based and label-free 3D detection (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2019_pseudo_14678,
  title = {{Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2020_hvnet_15634,
  title = {{HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2020_dsgn_15334,
  title = {{DSGN: Deep Stereo Geometry Network for 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2020_train_16373,
  title = {{Train in Germany, Test in the USA: Making 3D Object Detectors Generalize}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2021_rsn_17691,
  title = {{RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{aaai2022_afdetv2_1691,
  title = {{AFDetV2: Rethinking the Necessity of the Second Stage for Object Detection from Point Clouds}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/00969-afdetv2-rethinking-the-necessity-of-the-second-stage-for-object-detection-from-point-clouds/},
}

@inproceedings{cvpr2020_what_16487,
  title = {{What You See is What You Get: Exploiting Visibility for 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{iclr2020_pseudo_29284,
  title = {{Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=BJedHRVtPB},
}

@inproceedings{cvpr2023_omni3d_21747,
  title = {{Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22614},
}

@inproceedings{cvpr2023_octr_21743,
  title = {{OcTr: Octree-Based Transformer for 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22293},
}

@inproceedings{cvpr2024_safdnet_24681,
  title = {{SAFDNet: A Simple and Effective Network for Fully Sparse 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29829},
}

@inproceedings{aaai2023_lidarmultinet_4067,
  title = {{LidarMultiNet: Towards a Unified Multi-Task Network for LiDAR Perception}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25429},
}

@inproceedings{cvpr2020_ida_15666,
  title = {{IDA-3D: Instance-Depth-Aware 3D Object Detection From Stereo Vision for Autonomous Driving}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2021_lidar_17346,
  title = {{LiDAR-Aug: A General Rendering-Based Augmentation Framework for 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2021_pvgnet_17572,
  title = {{PVGNet: A Bottom-Up One-Stage 3D Object Detector With Integrated Multi-Level Features}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2020_dops_15331,
  title = {{DOPS: Learning to Detect 3D Objects and Predict Their 3D Shapes}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2023_link_21444,
  title = {{LinK: Linear Kernel for LiDAR-Based 3D Perception}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22454},
}

@inproceedings{aaai2024_di_5562,
  title = {{DI-V2X: Learning Domain-Invariant Representation for Vehicle-Infrastructure Collaborative 3D Object Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28105},
}

@inproceedings{neurips2022_fully_65580,
  title = {{Fully Sparse 3D Object Detection}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55348},
}

@inproceedings{cvpr2022_learning_19214,
  title = {{Learning To Detect Mobile Objects From LiDAR Scans Without Labels}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2024_three_25014,
  title = {{Three Pillars Improving Vision Foundation Model Distillation for Lidar}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30846},
}

@inproceedings{cvpr2024_commonsense_22998,
  title = {{Commonsense Prototype for Outdoor Unsupervised 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30453},
}

@inproceedings{aaai2024_sunshine_7440,
  title = {{Sunshine to Rainstorm: Cross-Weather Knowledge Distillation for Robust 3D Object Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28016},
}

@inproceedings{cvpr2024_cakdp_22941,
  title = {{CaKDP: Category-aware Knowledge Distillation and Pruning Framework for Lightweight 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29934},
}

@inproceedings{cvpr2024_improving_23770,
  title = {{Improving Distant 3D Object Detection Using 2D Box Supervision}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29651},
}

@inproceedings{cvpr2025_vikienet_28069,
  title = {{ViKIENet: Towards Efficient 3D Object Detection with Virtual Key Instance Enhanced Network}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35081},
}

@inproceedings{cvpr2025_learning_26761,
  title = {{Learning to Detect Objects from  Multi-Agent LiDAR Scans without Manual Labels}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33859},
}

@inproceedings{cvpr2024_an_22762,
  title = {{An Empirical Study of the Generalization Ability of Lidar 3D Object Detectors to Unseen Domains}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31845},
}

@inproceedings{cvpr2024_semoli_24759,
  title = {{SeMoLi: What Moves Together Belongs Together}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30270},
}

@inproceedings{cvpr2024_vsrd_25197,
  title = {{VSRD: Instance-Aware Volumetric Silhouette Rendering for Weakly Supervised 3D Object Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31171},
}

@inproceedings{neurips2024_uav3d_74083,
  title = {{UAV3D: A Large-scale 3D Perception Benchmark for Unmanned Aerial Vehicles}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/97488},
}

@inproceedings{aaai2025_seg2box_10709,
  title = {{Seg2Box: 3D Object Detection by Point-Wise Semantics Supervision}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33150},
}

@inproceedings{cvpr2025_mad_26832,
  title = {{MAD: Memory-Augmented Detection of 3D Objects}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33670},
}

@inproceedings{cvpr2024_weak_25269,
  title = {{Weak-to-Strong 3D Object Detection with X-Ray Distillation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30116},
}

@inproceedings{iclr2024_mixsup_34390,
  title = {{MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18685},
}

@inproceedings{neurips2024_ffam_74124,
  title = {{FFAM: Feature Factorization Activation Map for Explanation of 3D Detectors}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93413},
}

@inproceedings{aaai2025_nba3d_10082,
  title = {{NBA3D: Neighbor-Based Confidence Adjustment for 3D Rare Object Detection Using LiDAR}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32475},
}

@inproceedings{icml2025_towards_48954,
  title = {{Towards Learning to Complete Anything in Lidar}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43669},
}