2 citations · 2 across the 1 of their papers we have counts for
3 papers
cs.CV2024
PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images
Nanqing Liu, Xun Xu, Yongyi Su +2
Segment Anything Model (SAM) is an advanced foundational model for image segmentation, which is gradually being applied to remote sensing images (RSIs). Due to the domain gap betwe…
cs.CV2024
CLIP-Guided Source-Free Object Detection in Aerial Images
Nanqing Liu, Xun Xu, Yongyi Su +3
Domain adaptation is crucial in aerial imagery, as the visual representation of these images can significantly vary based on factors such as geographic location, time, and weather…
cs.CV2023★ 2 cited
Semi-Supervised Object Detection with Uncurated Unlabeled Data for Remote Sensing Images
Nanqing Liu, Xun Xu, Yingjie Gao +1
Annotating remote sensing images (RSIs) presents a notable challenge due to its labor-intensive nature. Semi-supervised object detection (SSOD) methods tackle this issue by generat…