… ENcoder Network (PEN-Net) for image inpainting by deep generative models. The PEN-Net
is built upon a U-Net structure, which can restore an image by encoding … -context encoder, …

… an improved image inpainting method based on a new encoder … images and ensure that the
semantic features of images are … In the encoder part of the discriminative network, moreover, …

… We propose a mutual encoder-decoder network for image inpainting. The CNN features
from the shallow layer are learned to represent textures and the features from deep layers …

… into the coarse inpainting network or the refinement inpainting network. The measurement
… the MSE in the coarse inpainting network is better than in the refinement inpainting network. …

… image inpainting. Combined with the characteristics of skip-connection [13] and Auto-Encoders,
the model consists of an encoder-… the image to be repaired into the encoder and encode …

… is based on encoder-decoder generative networks and is able to … image inpainting framework,
an end-to-end neural network, … image regions. (2) Different from the previous GAN-based …

… parts in images. In this paper, two new techniques for image inpainting techniques using
Deep Convolution Neural Networks (CNN) are proposed. In the first technique, a self-tuned …

… – a convolutional neural network trained to generate the contents of an arbitrary … On the
encoder side, we show that encoding just the context of an image patch and using the resulting …

… We first construct our baseline generative image inpainting network by reproducing and …
two parallel encoders as shown in Figure 4 based on Figure 2. The bottom encoder specifically …

… of image inpainting in different scenarios, and give a detailed analysis on the performance of
different inpainting … -based inpainting only updates masks in the encoding network, ignoring …