Edge Prior Multilayer Segmentation Network Based on Bayesian Framework In recent years, methods based on neural network have achieved excellent performance for image segmentation. However, segmentation around the edge area is still unsatisfactory when dealing with complex boundaries. This paper proposes an edge prior semantic segmentation architecture based on Bayesian framework. The entire framework is composed of three network structures, a likelihood network and an edge prior network at the front, followed by a constraint network. The likelihood network produces a rough segmentation result, which is later optimized by edge prior information, including the edge map and the edge distance. For the constraint network, the modified domain transform method is proposed, in which the diffusion direction is revised through the newly defined distance map and some added constraint conditions. Experiments about the proposed approach and several contrastive methods show that our proposed method had good performance and outperformed FCN in terms of average accuracy for 0.0209 on ESAR data set.

Edgeguided Hierarchically Nested Network for Realtime Semantic Segmentation Semantic segmentation requires both large region context information and rich spatial information. The former can be achieved by a deepenough network structure. However, most spatial information lost in repeated downsample operation in deep Convolutional Neural Networks cannot be easily recovered. In this paper, we propose a novel edgeguided hierarchically nested network to improve both speed and accuracy of realtime semantic segmentation. We introduce Edge Guidance Unit which aims to guide the decoder network to exploit highresolution clues, recover and refine spatial information with low additional computational cost. We also introduce a welldesigned Fusion Block to combine different resolution features along with edge guidance. In experiments we demonstrate that our network stabilizes the small object region while achieving a result of 72.7% mean IoU at 40 FPS on CityScapes test dataset.