Integrating two-dimensional (2D) and three-dimensional (3D) data is a significant challenge. Models tailored for 2D images, such as those based on convolutional neural networks, need to be revised for interpreting complex 3D environments. Models designed for 3D spatial data, like point cloud processors, often fail to effectively leverage the rich detail available in 2D imagery.…
