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PEPSI++: Fast and Lightweight Network for Image Inpainting
[article]
2020
arXiv
pre-print
Among the various generative adversarial network (GAN)-based image inpainting methods, a coarse-to-fine network with a contextual attention module (CAM) has shown remarkable performance. However, owing to two stacked generative networks, the coarse-to-fine network needs numerous computational resources such as convolution operations and network parameters, which result in low speed. To address this problem, we propose a novel network architecture called PEPSI: parallel extended-decoder path for
arXiv:1905.09010v4
fatcat:j562nzwoprhedipkghfhq7so7y