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Ensemble Dehazing Networks for Non-homogeneous Haze
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Image dehazing is one of the most challenging imaging inverse problems. Although deep learning methods produce compelling results, one of the most crucial practical challenge is that of non-homogeneous haze, which remains an open problem. To address this challenge, we propose 3 models that are inspired by ensemble techniques. First, we propose a DenseNet based single-encoder four-decoders structure denoted as EDN-3J, wherein among the four decoders, three of them output estimates of dehazed
doi:10.1109/cvprw50498.2020.00233
dblp:conf/cvpr/YuCGM20
fatcat:ezanxdrusrcedbq44psix5fsua