  The instance segmentation problem intends to precisely detect and delineate
objects in images. Most of the current solutions rely on deep convolutional
neural networks but despite this fact proposed solutions are very diverse. Some
solutions approach the problem as a network problem, where they use several
networks or specialize a single network to solve several tasks. A different
approach tries to solve the problem as an annotation problem, where the
instance information is encoded in a mathematical representation. This work
proposes a solution based in the DCME technique to solve the instance
segmentation with a single segmentation network. Different from others, the
segmentation network decoder is not specialized in a multi-task network.
Instead, the network encoder is repurposed to classify image objects, reducing
the computational cost of the solution.
