5 papers
DGTRSD & DGTRS-CLIP: A Dual-Granularity Remote Sensing Image-Text Dataset and Vision Language Foundation Model for Alignment
Weizhi Chen, Yupeng Deng, Jin Wei +7
Vision Language Foundation Models based on CLIP architecture for remote sensing primarily rely on short text captions, which often result in incomplete semantic representations. Al…
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…
IRSAMap:Towards Large-Scale, High-Resolution Land Cover Map Vectorization
Yu Meng, Ligao Deng, Zhihao Xi +9
With the enhancement of remote sensing image resolution and the rapid advancement of deep learning, land cover mapping is transitioning from pixel-level segmentation to object-base…
GLD-Road:A global-local decoding road network extraction model for remote sensing images
Ligao Deng, Yupeng Deng, Yu Meng +4
Road networks are crucial for mapping, autonomous driving, and disaster response. While manual annotation is costly, deep learning offers efficient extraction. Current methods incl…
Prompt-Driven Building Footprint Extraction in Aerial Images with Offset-Building Model
Kai Li, Yupeng Deng, Yunlong Kong +5
More accurate extraction of invisible building footprints from very-high-resolution (VHR) aerial images relies on roof segmentation and roof-to-footprint offset extraction. Existin…