Read and display a point cloud before augmentation using thehelperShowPointCloudWith3DBoxeshelper function, defined at the end of the example. augData = preview(cds); [ptCld,bboxes,labels] = deal(augData{1},aug
Deep structural information fusion for 3D object detection on LiDAR-camera systemPei AnJunxiong LiangKun YuBin FangJie Ma
多模态融合: DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection，这研究探讨了如何在自动驾驶领域中，通过整合激光雷达和相机数据进行三维物体检测，以提高检测精度和可靠性。面对现有技术的局限性，研究团队提出了一种创新的深度特征融合策略，旨在解决传统方法中出现的挑战，包括特征...
Object detection and transfer learning on point clouds using pretrained Complex-YOLOv4 models in MATLAB computer-visiondeep-learningmatlabyololidarobject-detectiontransfer-learningpretrained-modelslidar-object-detectionyolov4tiny-yolov4matlab-deep-learning ...
Focal loss for dense object detection (2017). Salehi, S. S. M., Erdogmus, D. & Gholipour, A. Tversky loss function for image segmentation using 3d fully convolutional deep networks. In International Workshop on Machine Learning in Medical Imaging 379–387 (Springer, 2017). Smith, L. N...
plane extraction, the acquisition of point clouds depends on light detection and ranging (LiDAR) or depth cameras, which are not affected by stair texture features and lighting conditions. However, LiDAR and binocular sensors are often expensive and still cannot solve the problem of severe occlusion...
The projection method converts the 3D LiDAR point cloud into a 2D plane representation, such as a range view or bird’s-eye view (BEV). The projected data can be processed using the standard 2D detection models and reduces the computational burden due to 3D convolution; however, there is ...
Stereo-LiDAR-CCVNorm: "3d lidar and stereo fusion using stereo matching network with conditional cost volume normalization", Wang et al., IROS, 2019. [Paper] [Code] [Bibtex] [Google Scholar] Pseudo-LiDAR++: "Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving", Yo...
The advantage of LiDAR lies in 3D modeling, wide detection range, and high detection accuracy. Therefore, deep learning target detection systems using LiDAR detectors are a hot research direction. However, there are still some problems in the current deep learning-based LiDAR detection systems. ...
3D building reconstruction without any manual intervention continues to be a scientific challenge, considering the various building styles and layout, the complicated backgrounds (e.g., building shadows and occlusions of vegetation), and the quality of the source data (e.g., the density of LiDAR ...