Referring Remote Sensing Image Segmentation (RRSIS) addresses the task of identifying ground objects guided by natural language descriptions. While Transformer-based architectures have shown promise, significant limitations remain in processing high-resolution imagery due to quadratic computational complexity and the l...
Shi-Miao Fan, Yi-Jie Zhang, Zhi-Ling Zhang et al.· International Conference on...· 0 citations
The complexity of object categories in high-resolution remote sensing frequently gives rise to discontinuous boundaries in segmentation results. Furthermore, the inability to model global contextual morphological continuities along strip objects is a primary cause of segmentation fractures. Therefore, we propose a remo...
Chun-Bo Chang, Xin-Lin Xie, Shen-Ran Guo et al.· Italian National Conference...· 0 citations
In recent years, encoder–decoder architectures have driven remarkable progress in remote sensing semantic segmentation. However, achieving both high accuracy and computational efficiency for high-resolution UAV imagery remains challenging. For Vision Transformer (ViT)-based models, the quadratic computational and memor...
Chang-Jian Deng, Jian Cheng, Zhi-Guo Yang et al.· IEEE Transactions on Geoscie...· 0 citations
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