Deep Variational Instance Segmentation

Understand

Instance Segmentation, which seeks to obtain both class and instance labels for each pixel in the input image, is a challenging task in computer vision.

• State-of-the-art algorithms often employ two separate stages, the first one generating object proposals and the second one recognizing and refining the boundaries.
• Further, proposals are usually based on detectors such as faster R-CNN which search for boxes in the entire image exhaustively.
• In this paper, we propose a novel algorithm that directly utilizes a fully convolutional network (FCN) to predict instance labels.