激光雷达感知论文趋势 2023–2026
点云检测
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 360 篇被归入该主题的论文。
主要结论
- 激光雷达感知论文从 2023 年的 84 篇增长到 2026 年的 100 篇，三年间扩大到约 1.2 倍。
- CVPR 是发激光雷达感知论文最多的会议，2023–2026 年共 242 篇，占四个会议总量的 67%。
- 交叉方向里涨得最快的是多模态大模型：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 17 篇。
- 在「自动驾驶」的 5 个主题里，它的 2026 年论文数排第 3；同组增长最快的运动规划是 2.4 倍，激光雷达感知是 1.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 10 | 5 | 2 | 67 | 84 |
| 2024 | 19 | 5 | 4 | 62 | 90 |
| 2025 | 21 | 5 | 7 | 53 | 86 |
| 2026 | 25 | 5 | 10 | 60 | 100 |
代表论文
按年份和会议均匀挑选，方便快速看到每一届的样貌
- NeurIPS 2026BiLi: Bridging the Last Mile in LiDAR Localization
- ICML 2026PACE: Post-Causal Entropy Modeling for Learned LiDAR Point Cloud Compression
- ICLR 2026GaussianFusion: Unified 3D Gaussian Representation for Multi-Modal Fusion Perception
- CVPR 2026Adaptive 3D Perception for Small Aerial Targets Under Sparse Sampling
- NeurIPS 2025Optimal Neural Compressors for the Rate-Distortion-Perception Tradeoff
- ICML 2025Towards Learning to Complete Anything in Lidar
- ICLR 2025Point Cluster: A Compact Message Unit for Communication-Efficient Collaborative Perception
- CVPR 2025DiskVPS: Vanishing Point Detector via Hough Transform in a Disk Region
- NeurIPS 2024Inference on the Change Point under a High Dimensional Covariance Shift
- ICML 2024How Learning by Reconstruction Produces Uninformative Features For Perception
- ICLR 2024CALICO: Self-Supervised Camera-LiDAR Contrastive Pre-training for BEV Perception
- CVPR 2024GLiDR: Topologically Regularized Graph Generative Network for Sparse LiDAR Point Clouds
- NeurIPS 2023Asynchrony-Robust Collaborative Perception via Bird's Eye View Flow
- ICML 2023Robust Perception through Equivariance
- ICLR 2023LiftedCL: Lifting Contrastive Learning for Human-Centric Perception
- CVPR 2023ALSO: Automotive Lidar Self-Supervision by Occupancy Estimation
- NeurIPS 2026CMI-Trans: Cross Modal Inconsistency-aware Transport for HSI-LiDAR Classification
- ICML 2026OBJVanish: Prompt-Driven Generation of Physically Realizable 3D LiDAR-Invisible Objects
- ICLR 2026Point-Focused Attention Meets Context-Scan State Space: Robust Biological Visual Perception for Point Cloud Representation
- CVPR 2026Bezier Degradation Modeling for LiDAR-based Human Motion Capture
全部激光雷达感知论文
共 241 篇，第 4 / 5 页
- CVPR 2024Point Cloud Pre-training with Diffusion Models
- CVPR 2024Point Transformer V3: Simpler Faster Stronger
- CVPR 2024PointInfinity: Resolution-Invariant Point Diffusion Models
- CVPR 2024PointOBB: Learning Oriented Object Detection via Single Point Supervision
- CVPR 2024Polarization Wavefront Lidar: Learning Large Scene Reconstruction from Polarized Wavefronts
- CVPR 2024PTT: Point-Trajectory Transformer for Efficient Temporal 3D Object Detection
- CVPR 2024RadarDistill: Boosting Radar-based Object Detection Performance via Knowledge Distillation from LiDAR Features
- CVPR 2024Resolution Limit of Single-Photon LiDAR
- CVPR 2024Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion
- CVPR 2024SeMoLi: What Moves Together Belongs Together
- CVPR 2024Single-View Scene Point Cloud Human Grasp Generation
- CVPR 2024SIRA: Scalable Inter-frame Relation and Association for Radar Perception
- CVPR 2024Sparse Views Near Light: A Practical Paradigm for Uncalibrated Point-light Photometric Stereo
- CVPR 2024Spherical Mask: Coarse-to-Fine 3D Point Cloud Instance Segmentation with Spherical Representation
- CVPR 2024StraightPCF: Straight Point Cloud Filtering
- CVPR 2024TASeg: Temporal Aggregation Network for LiDAR Semantic Segmentation
- CVPR 2024TetraSphere: A Neural Descriptor for O(3)-Invariant Point Cloud Analysis
- CVPR 2024Text2Loc: 3D Point Cloud Localization from Natural Language
- CVPR 2024Towards Robust 3D Object Detection with LiDAR and 4D Radar Fusion in Various Weather Conditions
- CVPR 2024TULIP: Transformer for Upsampling of LiDAR Point Clouds
- CVPR 2024TUMTraf V2X Cooperative Perception Dataset
- CVPR 2024Unsupervised Template-assisted Point Cloud Shape Correspondence Network
- CVPR 2024Visual Point Cloud Forecasting enables Scalable Autonomous Driving
- CVPR 2024Weak-to-Strong 3D Object Detection with X-Ray Distillation
- CVPR 2023ALSO: Automotive Lidar Self-Supervision by Occupancy Estimation
- CVPR 2023AnchorFormer: Point Cloud Completion From Discriminative Nodes
- CVPR 2023Attention-Based Point Cloud Edge Sampling
- CVPR 2023BEV-SAN: Accurate BEV 3D Object Detection via Slice Attention Networks
- CVPR 2023Bi-LRFusion: Bi-Directional LiDAR-Radar Fusion for 3D Dynamic Object Detection
- CVPR 2023Binarizing Sparse Convolutional Networks for Efficient Point Cloud Analysis
- CVPR 2023Building Rearticulable Models for Arbitrary 3D Objects From 4D Point Clouds
- CVPR 2023Collaboration Helps Camera Overtake LiDAR in 3D Detection
- CVPR 2023CP3: Channel Pruning Plug-In for Point-Based Networks
- CVPR 2023Curricular Object Manipulation in LiDAR-Based Object Detection
- CVPR 2023CXTrack: Improving 3D Point Cloud Tracking With Contextual Information
- CVPR 2023E2PN: Efficient SE(3)-Equivariant Point Network
- CVPR 2023Efficient Hierarchical Entropy Model for Learned Point Cloud Compression
- CVPR 2023FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer
- CVPR 2023Frequency-Modulated Point Cloud Rendering With Easy Editing
- CVPR 2023GD-MAE: Generative Decoder for MAE Pre-Training on LiDAR Point Clouds
- CVPR 2023Grad-PU: Arbitrary-Scale Point Cloud Upsampling via Gradient Descent With Learned Distance Functions
- CVPR 2023GraVoS: Voxel Selection for 3D Point-Cloud Detection
- CVPR 2023Hyperspherical Embedding for Point Cloud Completion
- CVPR 2023HypLiLoc: Towards Effective LiDAR Pose Regression With Hyperbolic Fusion
- CVPR 2023Implicit Surface Contrastive Clustering for LiDAR Point Clouds
- CVPR 2023Instant Domain Augmentation for LiDAR Semantic Segmentation
- CVPR 2023IterativePFN: True Iterative Point Cloud Filtering
- CVPR 2023LaserMix for Semi-Supervised LiDAR Semantic Segmentation
- CVPR 2023Learning To Measure the Point Cloud Reconstruction Loss in a Representation Space
- CVPR 2023LiDAR-in-the-Loop Hyperparameter Optimization
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查激光雷达感知在 CVPR 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "lidar-perception"}
常见问题
- 2023–2026 年四大会议一共有多少篇激光雷达感知论文？
- 共 360 篇，按年份分别是 2023 年 84 篇、2024 年 90 篇、2025 年 86 篇、2026 年 100 篇。
- NeurIPS 2026 有多少篇激光雷达感知论文？
- NeurIPS 2026 有 25 篇激光雷达感知论文，上一届是 21 篇。
- ICLR 2026 有多少篇激光雷达感知论文？
- ICLR 2026 有 5 篇激光雷达感知论文，上一届是 5 篇。
- ICML 2026 有多少篇激光雷达感知论文？
- ICML 2026 有 10 篇激光雷达感知论文，上一届是 7 篇。
- CVPR 2026 有多少篇激光雷达感知论文？
- CVPR 2026 有 60 篇激光雷达感知论文，上一届是 53 篇。
- 哪个会议的激光雷达感知论文最多？
- CVPR，2023–2026 年共 242 篇。