We present the first fully convolutional end-to-end solution for instance-aware semantic segmentation task. 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.

We devise the convolution neural network based fast algorithm to decrease no less than two CU partition modes in each CTU for full rate-distortion optimization (RDO) processing, thereby reducing the encoder's hardware complexity.