False: False Negative Samples Aware Contrastive Learning for Semantic Segmentation of High-Resolution Remote Sensing Image

2 code implementations • 15 Nov 2022 • Zhaoyang Zhang, Xuying Wang, Xiaoming Mei, Chao Tao, Haifeng Li

This indicates that the SSCL model has the ability to self-differentiate FNS and that the FALSE effectively mitigates the SCI in self-supervised contrastive learning.

Contrastive Learning Segmentation +1

SCAttNet: Semantic Segmentation Network with Spatial and Channel Attention Mechanism for High-Resolution Remote Sensing Images

1 code implementation • 19 Dec 2019 • Haifeng Li, Kaijian Qiu, Li Chen, Xiaoming Mei, Liang Hong, Chao Tao

High-resolution remote sensing images (HRRSIs) contain substantial ground object information, such as texture, shape, and spatial location.

Segmentation Semantic Segmentation

MAP-Net: Multi Attending Path Neural Network for Building Footprint Extraction from Remote Sensed Imagery

1 code implementation • 26 Oct 2019 • Qing Zhu, Cheng Liao, Han Hu, Xiaoming Mei, Haifeng Li

This paper proposes a novel multi attending path neural network (MAP-Net) for accurately extracting multiscale building footprints and precise boundaries.