Image completion involves removing unwanted portions of a given photograph. We propose a method of image completion on the Android phone using a small database to search for a matching image. SURF is employed in image matching and image registration. Fast Poisson blending is used to blend the registered database image with the original image.

In this paper, we present a novel automatic image completion solution in a greedy manner inspired by a primal sketch representation model. Firstly, an image is divided into structure (sketchable) components and texture (non-sketchable) components, and the missing structures, such as curves and corners, are predicted by tensor voting. Secondly, the textures along structural sketches are synthesi...

Image inpainting consists in recovering missing parts of an image. Since a color image is a D array, tensor completion methods are applicable to this problem. Tensor completion approach based on trace norm minimization can be useful when the fraction of missing pixels is not large, with the advantage that the training set is not required. Here, we demonstrate that the dictionary for sparse repr...

Binary neural associative memories are attractive for image processing because of their speed of operation for learning associations and for recalling them. We have added feedback to a feed-forward associa-tive memory, to produce a pattern completion network which performs translation-invariant pattern completion, and at the same time resolves contradictory image information. The image completi...

Image completion methods based on deep learning, such as Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs), have succeeded in producing semantically plausible results. However, existing facial image can either produce only one result or, although they provide multiple results, cannot attribute particular emotions to the We propose EC-GAN, a novel Emotion-Controllable GA...