Experiments are conducted on a series of remote sensing images (NWPU VHR-10). Detection & instance segmentation results demonstrate that our method provides better performance (significant improvement in accuracy) in terms of average precision (AP). The larger the value of AP is, the more accurate the prediction results and the better detection performance of the objects. Cascade Mask R-CNN framework with HRNet backbone for geospatial objects detection and instance segmentation from high-resolution remote sensing imagery.