Instance-sensitive Fully Convolutional Networks

Understand

Fully convolutional networks (FCNs) have been proven very successful for semantic segmentation, but the FCN outputs are unaware of object instances.

• In this paper, we develop FCNs that are capable of proposing instance-level segment candidates.
• In contrast to the previous FCN that generates one score map, our FCN is designed to compute a small set of instance-sensitive score maps, each of which is the outcome of a pixel-wise classifier of a relative position to instances.
• On top of these instance-sensitive score maps, a simple assembling module is able to output instance candidate at each position.