Learning Dual Multi-Scale Manifold Ranking for Semantic Segmentation of High-Resolution Images

Learning Dual Multi-Scale Manifold Ranking for Semantic Segmentation of High-Resolution Images

Semantic image segmentation has recently witnessed considerable progress by training deep convolutional neural networks (CNNs). The core issue of this technique is the limited capacity of CNNs to depict visual objects. Existing approaches tend to utilize approximate inference in a discrete domain or additional aides and do not have a global optimum guarantee. We propose the use of the multi-lab...

Multi Resolution Fuzzy Segmentation of Satellite Images

multi resolution fuzzy segmentation of satellite images

multi resolution fuzzy segmentation of satellite images

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ICNet for Real-Time Semantic Segmentation on High-Resolution Images

We focus on the challenging task of realtime semantic segmentation in this paper. It finds many practical applications and yet is with fundamental difficulty of reducing a large portion of computation for pixel-wise label inference. We propose an compressed-PSPNet-based image cascade network (ICNet) that incorporates multi-resolution branches under proper label guidance to address this challeng...