Vehicle Detection from 3D Lidar Using Fully Convolutional Network

Cited by (576)

Items 301–400 of 576

1. A Method for Synthetic LiDAR Generation to Create Annotated Datasets for Autonomous Vehicles Perception
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2. Learning from irregularly sampled data for endomicroscopy super-resolution: a comparative study of sparse and dense approaches
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3. 3D Vehicle Detection on an FPGA from LiDAR Point Clouds
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4. Vertex points are not enough: Monocular 3D object detection via intra- and inter-plane constraints
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5. Training a Fast Object Detector for LiDAR Range Images Using Labeled Data from Sensors with Higher Resolution
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6. Efficient Deep Neural Networks
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7. Improving 3D Object Detection with Channel-wise Transformer
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8. Multiattention Mechanism 3D Object Detection Algorithm Based on RGB and LiDAR Fusion for Intelligent Driving
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9. MB-Net: MergeBoxes for Real-Time 3D Vehicles Detection
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10. The TUBS Road User Dataset: A New LiDAR Dataset and its Application to CNN-based Road User Classification for Automated Vehicles
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11. 3D Backbone Network for 3D Object Detection.
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12. A Multi-Sensor Fusion Based 2D-Driven 3D Object Detection Approach for Large Scene Applications
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13. Accurate and Real-Time Object Detection Based on Bird's Eye View on 3D Point Clouds
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14. LIV-DeepSORT: Optimized DeepSORT for Multiple Object Tracking in Autonomous Vehicles Using Camera and LiDAR Data Fusion
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15. Multiscale Pillars Fusion for 4-D Radar Object Detection With Radar Data Enhancement
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16. Vulnerable Road User Detection for Roadside-Assisted Safety Protection: A Comprehensive Survey
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17. Moving-Least-Squares-Enhanced 3D Object Detection for 4D Millimeter-Wave Radar
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18. Vision technologies in autonomous vehicles: progress, methodologies, and key challenges
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19. 3D Instance Segmentation Using Deep Learning on RGB-D Indoor Data
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20. Triangle-Mesh-Rasterization-Projection (TMRP): An Algorithm to Project a Point Cloud onto a Consistent, Dense and Accurate 2D Raster Image
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23. Using a Combination of LiDAR, RADAR, and Image Data for 3D Object Detection in Autonomous Vehicles
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24. A deep learning-based binocular perception system
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25. HCNET: A Point Cloud Object Detection Network Based on Height and Channel Attention
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26. Hallucinating Robots: Inferring Obstacle Distances from Partial Laser Measurements
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27. A Two-Stage Adaptive Clustering Approach for 3D Point Clouds
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28. RTL3D: real‐time LIDAR‐based 3D object detection with sparse CNN
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29. Three-Dimensional Backbone Network for 3D Object Detection in Traffic Scenes
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30. Feature Sharing and Integration for Cooperative Cognition and Perception with Volumetric Sensors
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31. SyS3DS: Systematic Sampling of Large-Scale LiDAR Point Clouds for Semantic Segmentation in Forestry Robotics
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32. Distributed Distance-Based Formation-Motion Control of Unicycle Agents Without Orientation Measurements
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33. General spiking neural network framework for the learning trajectory from a noisy mmWave radar
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34. GAL: Graph-Induced Adaptive Learning for Weakly Supervised 3D Object Detection
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35. Auto-Points: Automatic Learning for Point Cloud Analysis With Neural Architecture Search
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36. Fully Convolutional Neural Networks for 3D Vehicle Detection Based on Point Clouds
    Lihua Wen, Kang-Hyun Jo · 2019 · Lecture notes in computer science
37. Integrating State-of-the-Art CNNs for Multi-Sensor 3D Vehicle Detection in Real Autonomous Driving Environments
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38. Learning from irregularly sampled data for endomicroscopy super-resolution: a comparative study of sparse and dense approaches
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39. Multi-target Detection based on Multi-sensor Redundancy and Dynamic Weight Distribution for Driverless Cars
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40. Research on Estimation Method of Geometric Features of Structured Negative Obstacle Based on Single-Frame 3D Laser Point Cloud
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41. LiDAR and Radar Sensor Fusion for Detection and Tracking of Dynamic Objects in Autonomous Vehicles using Probabilistic Occupancy Grid, YOLO and DeepSORT
    Zo.A.T. Rakotoniaina, Nacer Eddine Chelbi, Denis Gingras, Frederic Faulconnier · 2022 · IEEE International Conference on Intelligent Transportation Systems (ITSC)
42. Pillar-Based 3D Object Detection from Point Cloud with Multiattention Mechanism
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43. Window normalization: Enhancing point cloud understanding by unifying inconsistent point densities
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44. MOD: Multi-camera Based Local Position Estimation for Moving Objects Detection
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45. Vehicle Object Detection Based on RGB-Camera and Radar Sensor Fusion
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46. SVM
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47. Objects Detection Using Sensors Data Fusion in Autonomous Driving Scenarios
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48. Multi-Sensor 3D Object Box Refinement for Autonomous Driving
    Peiliang Li, Siqi Liu, Shaojie Shen · 2019 · arXiv (Cornell University)
49. State Estimation for Truck and Trailer Systems using Deep Learning
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50. Learning-Based Reflection-Aware Virtual Point Removal for Large-Scale 3D Point Clouds
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51. PCDR-DFF: multi-modal 3D object detection based on point cloud diversity representation and dual feature fusion
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52. Detection and Tracking Dynamic Vehicles for Autonomous Driving Based on 2-D Point Scans
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53. TinyLid: a RISC-V accelerated Neural Network For LiDAR Contaminant Classification in Autonomous Vehicle
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54. 3D-DEEP: 3-Dimensional Deep-learning based on elevation patterns for road scene interpretation
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55. A Fast Obstacle Detection Method by Fusion of Double-Layer Region Growing Algorithm and Grid-SECOND Detector
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56. GridNet‐3D: A Novel Real‐Time 3D Object Detection Algorithm Based on Point Cloud
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57. Stereo VoVNet-CNN for 3D object detection
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58. Detection of Outliers in LiDAR Data Acquired by Multiple Platforms over Sorghum and Maize
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60. Efficient graph attentional network for 3D object detection from Frustum-based LiDAR point clouds
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62. Bean Split Ratio for Dry Bean Canning Quality and Variety Analysis
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64. Interest point detection from multi‐beam light detection and ranging point cloud using unsupervised convolutional neural network
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65. MSDPN: Monocular Depth Prediction with Partial Laser Observation using Multi-stage Neural Networks
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66. Object Detection based on LIDAR Temporal Pulses using Spiking Neural Networks
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67. Unsupervised Data Imputation via Variational Inference of Deep Subspaces
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70. Benchmark Analysis of Deep Learning-based 3D Object Detectors on NVIDIA Jetson Platforms
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71. Developing the GoogleNet neural network for the detection and recognition of unmanned aerial vehicles in the data Fusion System
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73. Pruning CNNs for LiDAR-based Perception in Resource Constrained Environments
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75. AEC3D: An Efficient and Compact Single Stage 3D Multiobject Detector for Autonomous Driving
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76. Pyramid Learnable Tokens for 3D LiDAR Place Recognition
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83. Applications of Convolutional Neural Networks to Extracting Oracle Bone Inscriptions from Three-Dimensional Models
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85. Hash-Based Gaussian Mixture Model (HGMM) for Roadside LiDAR Smart Infrastructure Applications
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88. Disentangling and Vectorization: A 3D Visual Perception Approach for Autonomous Driving Based on Surround-View Fisheye Cameras
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