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[CVPR2019]Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression
時間 2020-12-25
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IoU和GIoU作爲Loss的具體公式 GIoU很容易理解,就多了一個兩個BBox所佔最大面積A1,與並集的區別在於多算了不屬於BBox的一部分面積A2,就用A2除以A1,得到一個比例P1,paper中的意思是這個比例代表預測BBox與真實BBox的迴歸效果,效果也好比值越低,最後用傳統的IoU減去P1得到GIoU。
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相關文章
1.
Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression 論文
2.
Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression
3.
論文:Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression 閱讀筆記
4.
[論文閱讀]Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression
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The Lovasz-Softmax loss: A tractable surrogate for the optimization of the ´ intersection-over-union
8.
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9.
Monocular 3D Object Detection and Box Fitting Trained End-to-End Using Intersection-over-Union Loss
10.
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