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20202026
most citedLinear Attention Mechanism: An Efficient Attention for Semantic Segmentation

20 citations · 25 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

AeroReformer2: Spoken-Query Referring Segmentation for Aerial Images

Rui Li, Chenxi Duan, Haoyang Yang

Spoken language offers a natural, hands-free interface for specifying an arbitrary target in dense remote-sensing imagery, yet existing referring remote-sensing image segmentation…

cs.CV2021

Scale-aware Neural Network for Semantic Segmentation of Multi-resolution Remote Sensing Images

Libo Wang, Ce Zhang, Rui Li +3

Assigning geospatial objects with specific categories at the pixel level is a fundamental task in remote sensing image analysis. Along with rapid development in sensor technologies…

cs.CV2021

ABCNet: Attentive Bilateral Contextual Network for Efficient Semantic Segmentation of Fine-Resolution Remote Sensing Images

Rui Li, Chenxi Duan

Semantic segmentation of remotely sensed images plays a crucial role in precision agriculture, environmental protection, and economic assessment. In recent years, substantial fine-…

cs.CV20205 cited

Multi-Head Linear Attention Generative Adversarial Network for Thin Cloud Removal

Chenxi Duan, Rui Li

In remote sensing images, the existence of the thin cloud is an inevitable and ubiquitous phenomenon that crucially reduces the quality of imageries and limits the scenarios of app…

cs.CV202020 cited

Linear Attention Mechanism: An Efficient Attention for Semantic Segmentation

Rui Li, Jianlin Su, Chenxi Duan +1

In this paper, to remedy this deficiency, we propose a Linear Attention Mechanism which is approximate to dot-product attention with much less memory and computational costs. The e…