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the mask branch only adds a small computational overhead, enabling a fast system and rapid experimentation. In principle Mask R-CNN is an intuitive extension of Faster R-CNN, yet constructing the mask branch properly iscriticalforgoodresults. Mostimportantly,FasterR-CNN was not designed for pixel-to-pixel alignment between net-work inputs and outputs.
This paper proposes a general object instance segmentation model, which can detect + segment at the same time with a speed of 5 FPS. Based on fast RCNN, a mask prediction branch (FCN) is added parallel to the boundingbox prediction branch. It can be used in other tasks, such as human posture estimation. There is no fancy tricks.
20/3/2017, · The method, called Mask R-CNN, extends Faster R-CNN by adding a branch for predicting an object mask in parallel with the existing branch for bounding box recognition. Mask R-CNN is simple to train and adds only a small overhead to Faster R-CNN, running at 5 fps.