{"total":47,"rows":[{"id":"2109.00182","title":"You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors","created":"2021-09-01","cited_by_count":68,"area":null},{"id":"2203.09065","title":"STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Dataset","created":"2022-03-17","cited_by_count":53,"area":null},{"id":"2103.03046","title":"PointGuard: Provably Robust 3D Point Cloud Classification","created":"2021-03-04","cited_by_count":49,"area":null},{"id":"2106.02377","title":"A Survey on Deep Domain Adaptation for LiDAR Perception","created":"2021-06-04","cited_by_count":47,"area":null},{"id":"2304.10406","title":"LiDAR-NeRF: Novel LiDAR View Synthesis via Neural Radiance Fields","created":"2023-04-20","cited_by_count":47,"area":null},{"id":"2304.14811","title":"NeRF-LiDAR: Generating Realistic LiDAR Point Clouds with Neural Radiance Fields","created":"2023-04-28","cited_by_count":44,"area":null},{"id":"2106.04180","title":"Image2Point: 3D Point-Cloud Understanding with 2D Image Pretrained Models","created":"2021-06-08","cited_by_count":41,"area":null},{"id":"2111.15242","title":"ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenation","created":"2021-11-30","cited_by_count":41,"area":null},{"id":"2111.10990","title":"Imperceptible Transfer Attack and Defense on 3D Point Cloud Classification","created":"2021-11-22","cited_by_count":36,"area":null},{"id":"2207.09763","title":"GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation","created":"2022-07-20","cited_by_count":35,"area":null},{"id":"2210.15291","title":"Isometric 3D Adversarial Examples in the Physical World","created":"2022-10-27","cited_by_count":25,"area":null},{"id":"2112.12252","title":"Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles","created":"2021-12-22","cited_by_count":22,"area":null},{"id":"2210.08738","title":"PCGen: Point Cloud Generator for LiDAR Simulation","created":"2022-10-17","cited_by_count":20,"area":null},{"id":"2404.04050","title":"No Time to Train: Empowering Non-Parametric Networks for Few-shot 3D Scene Segmentation","created":"2024-04-05","cited_by_count":18,"area":null},{"id":"2309.11039","title":"Federated Learning in Intelligent Transportation Systems: Recent Applications and Open Problems","created":"2023-09-20","cited_by_count":15,"area":null},{"id":"2205.15225","title":"Few-shot Class-incremental Learning for 3D Point Cloud Objects","created":"2022-05-30","cited_by_count":13,"area":null},{"id":"2301.12515","title":"LiDAR-CS Dataset: LiDAR Point Cloud Dataset with Cross-Sensors for 3D Object Detection","created":"2023-01-29","cited_by_count":13,"area":null},{"id":"2111.11976","title":"KTNet: Knowledge Transfer for Unpaired 3D Shape Completion","created":"2021-11-23","cited_by_count":9,"area":null},{"id":"2303.01038","title":"Neural Intrinsic Embedding for Non-rigid Point Cloud Matching","created":"2023-03-02","cited_by_count":9,"area":null},{"id":"2308.07546","title":"3DHacker: Spectrum-based Decision Boundary Generation for Hard-label 3D Point Cloud Attack","created":"2023-08-15","cited_by_count":9,"area":null},{"id":"2208.14603","title":"Blind Quality Assessment of 3D Dense Point Clouds with Structure Guided Resampling","created":"2022-08-31","cited_by_count":7,"area":null},{"id":"2303.01899","title":"Quantifying the LiDAR Sim-to-Real Domain Shift: A Detailed Investigation Using Object Detectors and Analyzing Point Clouds at Target-Level","created":"2023-03-03","cited_by_count":7,"area":null},{"id":"2407.11011","title":"Toward Availability Attacks in 3D Point Clouds","created":"2024-06-26","cited_by_count":7,"area":null},{"id":"2107.04291","title":"Task-Aware Sampling Layer for Point-Wise Analysis","created":"2021-07-09","cited_by_count":6,"area":null},{"id":"2408.01356","title":"Balanced Residual Distillation Learning for 3D Point Cloud Class-Incremental Semantic Segmentation","created":"2024-08-02","cited_by_count":6,"area":null},{"id":"2207.00191","title":"Data generation using simulation technology to improve perception mechanism of autonomous vehicles","created":"2022-07-01","cited_by_count":5,"area":null},{"id":"2107.01469","title":"Scene-aware Learning Network for Radar Object Detection","created":"2021-07-03","cited_by_count":4,"area":null},{"id":"2111.14067","title":"PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds","created":"2021-11-28","cited_by_count":4,"area":null},{"id":"2210.09728","title":"3D Scalable Quantum Convolutional Neural Networks for Point Cloud Data Processing in Classification Applications","created":"2022-10-18","cited_by_count":4,"area":null},{"id":"2307.16361","title":"Benchmarking and Analyzing Robust Point Cloud Recognition: Bag of Tricks for Defending Adversarial Examples","created":"2023-07-31","cited_by_count":4,"area":null},{"id":"2408.14253","title":"Text3DAug -- Prompted Instance Augmentation for LiDAR Perception","created":"2024-08-26","cited_by_count":4,"area":null},{"id":"2107.13087","title":"DCL: Differential Contrastive Learning for Geometry-Aware Depth Synthesis","created":"2021-07-27","cited_by_count":3,"area":null},{"id":"2104.02979","title":"Few-Shot Meta-Learning on Point Cloud for Semantic Segmentation","created":"2021-04-07","cited_by_count":2,"area":null},{"id":"2303.12743","title":"DR.CPO: Diversified and Realistic 3D Augmentation via Iterative Construction, Random Placement, and HPR Occlusion","created":"2023-03-20","cited_by_count":2,"area":null},{"id":"2308.05525","title":"Robustifying Point Cloud Networks by Refocusing","created":"2023-08-10","cited_by_count":2,"area":null},{"id":"2310.03360","title":"CSI: Enhancing the Robustness of 3D Point Cloud Recognition against Corruption","created":"2023-10-05","cited_by_count":1,"area":null},{"id":"2505.17959","title":"Mind the Domain Gap: Measuring the Domain Gap Between Real-World and Synthetic Point Clouds for Automated Driving Development","created":"2025-05-23","cited_by_count":1,"area":null},{"id":"2506.09510","title":"Generalized Gaussian Entropy Model for Point Cloud Attribute Compression with Dynamic Likelihood Intervals","created":"2025-06-11","cited_by_count":1,"area":null},{"id":"2511.02994","title":"Comprehensive Assessment of LiDAR Evaluation Metrics: A Comparative Study Using Simulated and Real Data","created":"2025-11-04","cited_by_count":1,"area":null},{"id":"2109.07324","title":"PointManifoldCut: Point-wise Augmentation in the Manifold for Point Clouds","created":"2021-09-15","cited_by_count":0,"area":null},{"id":"2202.02666","title":"Simulation-to-Reality domain adaptation for offline 3D object annotation on pointclouds with correlation alignment","created":"2022-02-06","cited_by_count":0,"area":null},{"id":"2312.06113","title":"SimMining-3D: Altitude-Aware 3D Object Detection in Complex Mining Environments: A Novel Dataset and ROS-Based Automatic Annotation Pipeline","created":"2023-12-11","cited_by_count":0,"area":null},{"id":"2406.01337","title":"ARCH2S: Dataset, Benchmark and Challenges for Learning Exterior Architectural Structures from Point Clouds","created":"2024-06-03","cited_by_count":0,"area":null},{"id":"2506.05009","title":"Point Cloud Segmentation of Agricultural Vehicles using 3D Gaussian Splatting","created":"2025-06-05","cited_by_count":0,"area":null},{"id":"2506.17378","title":"A workflow for generating synthetic LiDAR datasets in simulation environments","created":"2025-06-20","cited_by_count":0,"area":null},{"id":"2509.02904","title":"High-Fidelity Digital Twins for Bridging the Sim2Real Gap in LiDAR-Based ITS Perception","created":"2025-09-03","cited_by_count":0,"area":null},{"id":"2510.17068","title":"ProDAT: Progressive Density-Aware Tail-Drop for Point Cloud Coding","created":"2025-10-20","cited_by_count":0,"area":null}],"next_cursor":null}