5 citations · 9 across the 6 of their papers we have counts for
4 papers · 1 filter
DragOSM: Extract Building Roofs and Footprints from Aerial Images by Aligning Historical Labels
Kai Li, Xingxing Weng, Yupeng Deng +4
Extracting polygonal roofs and footprints from remote sensing images is critical for large-scale urban analysis. Most existing methods rely on segmentation-based models that assume…
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…
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…