Box2Seg: Attention weighted loss and discriminative feature learning for weakly supervised segmentation
We propose a weakly supervised approach to semantic segmentation using bounding box annotations. Bounding boxes are treated as noisy labels for the foreground objects. We predict a per-class attention map that saliently guides the per-pixel cross entropy loss to focus on foreground pixels and refine...
| 主要な著者: | , , , , |
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| フォーマット: | Conference item |
| 言語: | English |
| 出版事項: |
Springer International Publishing
2020
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