4 citations · 7 across the 6 of their papers we have counts for
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cs.CV2020
AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
Yonggan Fu, Wuyang Chen, Haotao Wang +3
The compression of Generative Adversarial Networks (GANs) has lately drawn attention, due to the increasing demand for deploying GANs into mobile devices for numerous applications…
eess.IV2020
Multi-modal Datasets for Super-resolution
Haoran Li, Weihong Quan, Meijun Yan +3
Nowdays, most datasets used to train and evaluate super-resolution models are single-modal simulation datasets. However, due to the variety of image degradation types in the real w…