Junjue-Wang/FactSeg
[TGRS 2021] FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery
FactSeg helps geospatial analysts and remote sensing professionals accurately identify and map very small objects like vehicles, buildings, or infrastructure elements in satellite or aerial images. It takes large-scale remote sensing imagery as input and outputs precise segmentation masks, clearly outlining these small objects. This is ideal for tasks requiring fine-grained mapping and object detection from overhead views.
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Use this if you need to precisely detect and delineate small, critical objects within vast satellite or aerial photographs.
Not ideal if your primary goal is general land cover classification or detecting large, easily visible features in remote sensing data.
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Language
Python
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Last pushed
Nov 11, 2022
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