Box2Seg: Attention weighted loss and discriminative feature learning for weakly supervised segmentation

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...

Полное описание

Библиографические подробности
Главные авторы:	Kulharia, V, Chandra, S, Agrawal, A, Torr, PHS, Tyagi, A
Формат:	Conference item
Язык:	English
Опубликовано:	Springer International Publishing 2020

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