Target detection method and device and corresponding model training method and device
A target detection and model technology, applied in the field of target detection, can solve the problems of not being able to identify large-category targets, and not being able to identify large or medium-sized vehicles, so as to improve detection accuracy, realize large-category target detection, and alleviate long tails effect of effect
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[0048]Using lidar to detect targets can use volume element-based neural network voxelnet, pointpillars-based algorithm pointpillars, sparse convolution SECOND (Sparsely Embedded Convolutional Detection, sparsely embedded convolution detection) and other schemes, these schemes are based on volume elements Feature extraction methods such as voxelized features or 3D convolutions are used to extract features from point clouds, and then use RPN (RegionProposalNetwork, feature stacking to perform region generation network) from the perspective of bev (bird's eye view) to perform target regression and Classification. What needs to be explained here is that the regression in the field of target detection refers to solving the determination of the detection frame as a mathematical regression problem, and the detection frame refers to the smallest bounding box that can determine the target, for example, in 2D scenes, it is usually A rectangle, usually a cuboid in a 3D scene.
[0049] H...
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