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20202024
most citedUNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery

1.3k citations · 2.2k across the 8 of their papers we have counts for

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Showing 2021 · cs.CVShow all

5 papers · 2 filters

cs.CV2021★ 244 cited

Building extraction with vision transformer

Libo Wang, Shenghui Fang, Rui Li +1

As an important carrier of human productive activities, the extraction of buildings is not only essential for urban dynamic monitoring but also necessary for suburban construction…

cs.CV2021★ 1.3k cited

UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery

Libo Wang, Rui Li, Ce Zhang +4

Semantic segmentation of remotely sensed urban scene images is required in a wide range of practical applications, such as land cover mapping, urban change detection, environmental…

cs.CV2021★ 9 cited

Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images

Libo Wang, Rui Li, Dongzhi Wang +3

Semantic segmentation from very fine resolution (VFR) urban scene images plays a significant role in several application scenarios including autonomous driving, land cover classifi…

cs.CV2021★ 415 cited

A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images

Libo Wang, Rui Li, Chenxi Duan +3

The fully convolutional network (FCN) with an encoder-decoder architecture has been the standard paradigm for semantic segmentation. The encoder-decoder architecture utilizes an en…

cs.CV2021★ 2 cited

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…