Jul 19, 2023 · In this paper, we propose a foreground-aware relation network (FarSeg++) from the perspectives of relation-based, optimization-based, and objectness-based ...

Nov 19, 2020 · In this paper, we argue that the problems lie on the lack of foreground modeling and propose a foreground-aware relation network (FarSeg)

The main challenges of object segmentation in the HSR remote sensing imagery. (1) larger-scale variation. (2) foreground- background imbalance. (3) intra-class ...

This is an official implementation of FarSeg in our CVPR 2020 paper Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial ...

FarSeg++, the foreground-aware relation network is proposed for geospatial object segmentation in HSR remote sensing imagery, which explicitly models the ...

This paper argues that the problems lie on the lack of foreground modeling and proposes a foreground-aware relation network (FarSeg) from the perspectives ...

PDF | Geospatial object segmentation, as a particular semantic segmentation task, always faces with larger-scale variation, larger intra-class variance.

1) FarSeg++, the foreground-aware relation network is proposed for geospatial object segmentation in HSR remote sensing imagery, which explicitly models the.

The experimental results suggest that FarSeg++ is superior to the state-of-the-art generic semantic segmentation methods and can achieve a better trade-off ...

In this paper, we argue that the problems lie on the lack of foreground modeling and propose a foreground-aware relation network (FarSeg)