We present a novel approach for completing and reconstructing 3D shapes from incomplete scanned data by using deep neural networks. Rather than being trained on supervised completion tasks applied testing shape, the network is optimized scratch single shape to fully adapt complete missing contextual guidance known regions. The ability an untrained usually referred as prior . In this article, we...

This paper investigates segmentation of images and videos using graph cuts and shape priors. Graph cuts is used to find the global optimum of a cost function based on the region and boundary properties of the image or video. The region and boundary properties are estimated using certain pixels marked by the user. A shape prior term is added to this cost function to bias the solution towards a k...