Image inpainting technique is that repairs damaged area or remove areas in an image. In order to deal with this kind of problems, not only a robust image inpainting algorithm should be used, technique of structure generation is also needs to adopt in inpainting procedure. In this paper, we extend an exemplar-based image inpainting method by incorporating Bézier curves to construct missing edge ...

Deep neural networks have been successfully applied to problems such as image segmentation, image super-resolution, coloration and image inpainting. In this work we propose the use of convolutional neural networks (CNN) for image inpainting of large regions in high-resolution textures. Due to limited computational resources processing high-resolution images with neural networks is still an open...

Image inpainting refers to the task of filling in the missing or damaged regions of an image in an undetectable manner. There are a large variety of image inpainting algorithms existing in the literature. They can broadly be grouped into two categories such as Partial Differential Equation (PDE) based algorithms and Exemplar based Texture synthesis algorithms. However no recent study has been u...

We develop in this paper a generic Bayesian framework for the joint estimation of motion and recovery of missing data in a damaged video sequence. Using standard maximum a posteriori to variational formulation rationale, we derive generic minimum energy formulations for the estimation of a reconstructed sequence as well as motion recovery. We instantiate these energy formulations and from their...

Image inpainting refers to the set of techniques which include filling-in of missing area (known as holes) in a picture such that modifications made to the picture are unnoticeable. The algorithms for image inpainting that are proposed in the literature are rooted on the concept to fill-in the holes by means of available information in the surroundings. This information can be automatically det...

The filling-in effect of diffusion processes has been successfully used in many image analysis applications. Examples include image reconstructions in inpainting-based compression or dense optic flow computations. As an interesting side effect of diffusion-based inpainting, the interpolated data are smooth, even if the known image data are noisy: Inpainting averages information from noisy sourc...

Video completion is a computer vision technique to recover the missing values in video sequences by filling the unknown regions with the known information. In recent research, tensor completion, a generalization of matrix completion for higher order data, emerges as a new solution to estimate the missing information in video with the assumption that the video frames are homogenous and correlate...

In this paper, we present a technique for automatic color image inpainting, the art of modifying an image-region in a non-detectable form. The main algorithm is based on the theory of projections onto convex sets (POCS). The image and its wavelet transform are projected onto each other after applying suitable constraints in each domain. This technique exploits the frequency-spatial representati...

We discuss an extension of our method image inpainting based on coherence transport. For the latter method the pixels of the inpainting domain have to be serialized into an ordered list. Until now, to induce the serialization we have used the distance to boundary map. But there are inpainting problems where the distance to boundary serialization causes unsatisfactory inpainting results. In the ...

In video conferencing, eye gaze correction is beneficial for effective communication. In this era, video conferencing at homes using laptops is straightforward. In this paper, we propose an eye gaze correction method with a low-cost simple setup using Kinect v2. Our method detects an ellipse that connects edge points of the face after identifying several feature points within the face using Kin...