Scene Understanding Based on High-Order Potentials and Generative Adversarial Networks

Xiaoli Zhao, Guozhong Wang, Jiaqi Zhang, Xiang Zhang
2018 Advances in Multimedia  
Scene understanding is to predict a class label at each pixel of an image. In this study, we propose a semantic segmentation framework based on classic generative adversarial nets (GAN) to train a fully convolutional semantic segmentation model along with an adversarial network. To improve the consistency of the segmented image, the high-order potentials, instead of unary or pairwise potentials, are adopted. We realize the high-order potentials by substituting adversarial network for CRF model,
more » ... which can continuously improve the consistency and details of the segmented semantic image until it cannot discriminate the segmented result from the ground truth. A number of experiments are conducted on PASCAL VOC 2012 and Cityscapes datasets, and the quantitative and qualitative assessments have shown the effectiveness of our proposed approach.
doi:10.1155/2018/8207201 fatcat:tjaj4et2orejjfxa3vcml6dtqu