Abstract: The present disclosure provides a ground object segmentation method based on a residual module and an attention mechanism, and a related apparatus, and relates to the field of remote sensing (RS) ground object segmentation technologies. The method includes the following steps: obtaining a to-be-segmented RS image; and inputting the to-be-segmented RS image into a trained ground object segmentation model to obtain a ground object segmentation result, where the ground object segmentation model is a network model obtained based on a U-Net neural network and with reference to the residual module and an attention module. In the present disclosure, a U-Net model with reference to a residual network structure and the attention mechanism is used.