dfqytcom / 2021-3d-object-detection Goto Github PK

This project forked from umd-fire-coml/2021-3d-object-detection

This product identifies and labels 3D Objects in images of every day settings, such as cars, trees, bikes, pedestrians, etc. This product makes use of a UNet, which is a Convolutional Neural Network, to identify objects, given voxel data. Our product first takes point cloud data from the SemanticKITTI dataset, and converts it to voxels. For the sake of simplicity, a voxel can be described as a 3d pixel. We visualize these voxels as cubes, each cube containing spatial information in 3 dimensions.