Abstract

We present the fifirst fully convolutional end-to-end solution for instance-aware semantic segmentation task. It inherits all the merits of FCNs for semantic segmentation [29] and instance mask proposal [5]. It detects and segments the object instances jointly and simultanoulsy. By the introduction of position-senstive inside/outside score maps, the underlying convolutional representation is fully shared between the two sub-tasks, as well as between all regions of interest. The proposed network is highly integrated and achieves state-of-the-art performance in both accuracy and effificiency. It wins the COCO 2016 segmentation competition by a large margin. Code would be released at https: //github.com/daijifeng001/TA-FCN