Reversible Recursive Instance-level Object Segmentation

CVPR 2016 Xiaodan LiangYunchao WeiXiaohui ShenZequn JieJiashi FengLiang LinShuicheng Yan

In this work, we propose a novel Reversible Recursive Instance-level Object Segmentation (R2-IOS) framework to address the challenging instance-level object segmentation task. R2-IOS consists of a reversible proposal refinement sub-network that predicts bounding box offsets for refining the object proposal locations, and an instance-level segmentation sub-network that generates the foreground mask of the dominant object instance in each proposal... (read more)

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