70 citations · 70 across the 5 of their papers we have counts for
5 papers
SCLNet: A Scale-Robust Complementary Learning Network for Object Detection in UAV Images
Xuexue Li
Most recent UAV (Unmanned Aerial Vehicle) detectors focus primarily on general challenge such as uneven distribution and occlusion. However, the neglect of scale challenges, which…
Insight Any Instance: Promptable Instance Segmentation for Remote Sensing Images
Xuexue Li
Instance segmentation of remote sensing images (RSIs) is an essential task for a wide range of applications such as land planning and intelligent transport. Instance segmentation o…
RingMo-Aerial: An Aerial Remote Sensing Foundation Model With Affine Transformation Contrastive Learning
Wenhui Diao, Haichen Yu, Kaiyue Kang +8
Aerial Remote Sensing (ARS) vision tasks present significant challenges due to the unique viewing angle characteristics. Existing research has primarily focused on algorithms for s…
Twin Deformable Point Convolutions for Point Cloud Semantic Segmentation in Remote Sensing Scenes
Yong-Qiang Mao, Hanbo Bi, Xuexue Li +4
Thanks to the application of deep learning technology in point cloud processing of the remote sensing field, point cloud segmentation has become a research hotspot in recent years,…
OGMN: Occlusion-guided Multi-task Network for Object Detection in UAV Images
Xuexue Li, Wenhui Diao, Yongqiang Mao +4
Occlusion between objects is one of the overlooked challenges for object detection in UAV images. Due to the variable altitude and angle of UAVs, occlusion in UAV images happens mo…