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Deep Back-Projection Networks for Super-Resolution
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
The feed-forward architectures of recently proposed deep super-resolution networks learn representations of low-resolution inputs, and the non-linear mapping from those to high-resolution output. However, this approach does not fully address the mutual dependencies of low-and high-resolution images. We propose Deep Back-Projection Networks (DBPN), that exploit iterative up-and downsampling layers, providing an error feedback mechanism for projection errors at each stage. We construct
doi:10.1109/cvpr.2018.00179
dblp:conf/cvpr/HarisSU18
fatcat:bo24jbi6sjanzmqn6qtstctt4y