Web: http://arxiv.org/abs/2201.11996

Jan. 31, 2022, 2:10 a.m. | Kuldeep Purohit, Srimanta Mandal, A. N. Rajagopalan

cs.CV updates on arXiv.org arxiv.org

Efficiency of gradient propagation in intermediate layers of convolutional
neural networks is of key importance for super-resolution task. To this end, we
propose a deep architecture for single image super-resolution (SISR), which is
built using efficient convolutional units we refer to as mixed-dense connection
blocks (MDCB). The design of MDCB combines the strengths of both residual and
dense connection strategies, while overcoming their limitations. To enable
super-resolution for multiple factors, we propose a scale-recurrent framework
which reutilizes the filters learnt …

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