Semantic Stereo Matching With Pyramid Cost Volumes

ICCV 2019 Zhenyao Wu Xinyi Wu Xiaoping Zhang Song Wang Lili Ju

The accuracy of stereo matching has been greatly improved by using deep learning with convolutional neural networks. To further capture the details of disparity maps, in this paper, we propose a novel semantic stereo network named SSPCV-Net, which includes newly designed pyramid cost volumes for describing semantic and spatial information on multiple levels... (read more)

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