Multimodal vehicle detection: fusing 3D-LIDAR and color camera data

ImageNet classification with deep convolutional neural networks

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You Only Look Once: Unified, Real-Time Object Detection

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YOLO9000: Better, Faster, Stronger

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Rapid object detection using a boosted cascade of simple features

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Are we ready for autonomous driving? The KITTI vision benchmark suite

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Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

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Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges

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Deep learning for object detection and scene perception in self-driving cars: Survey, challenges, and open issues

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Multi-Sensor Fusion in Automated Driving: A Survey

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Deep Learning Sensor Fusion for Autonomous Vehicle Perception and Localization: A Review

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A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets

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Multimodal Multi-Sensor Camera-LiDAR Fusion for 3D Object Detection in Autonomous Vehicles

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LiDAR-camera fusion for multi-modal 3D object detection

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Deep learning multi-modal fusion based 3D object detection

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UVFusion: A Unified Framework for Voxel-Aligned LiDAR–Camera Fusion in 3-D Object Detection

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3D Vehicle Detection Algorithm Based on Multimodal Decision-Level Fusion

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Semantic-Enhanced and Temporally Refined Bidirectional BEV Fusion for LiDAR–Camera 3D Object Detection

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MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object Detection

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DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection

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RVF3D: ROI-Driven Vision Transformer Fusion for Multi-Modal 3D Object Detection in Autonomous Vehicles

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LIDAR–camera fusion for road detection using fully convolutional neural networks

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