Subtitles are crucial for video content understanding. However, a large amount of videos have only burned-in, hardcoded subtitles that prevent re-editing, translation, etc. In this paper, we construct deep-learning-based system the inverse conversion burned-in subtitle to file and an inpainted video, by coupling three deep neural networks (CTPN, CRNN, EdgeConnect). We evaluated performance prop...

There are many existing image inpainting algorithms in which the repaired area should be manually determined by users. Aiming at this drawback of the traditional image inpainting algorithms, this paper proposes an automatic image inpainting algorithm which automatically identifies the repaired area by fuzzy C-mean (FCM) algorithm. FCM algorithm classifies the image pixels into a number of categ...

For few-shot learning, it is still a critical challenge to realize photo-realistic face visually dubbing on high-resolution videos. Previous works fail generate high-fidelity results. To address the above problem, this paper proposes Deformation Inpainting Network (DINet) for dubbing. Different from previous relying multiple up-sample layers directly pixels latent embeddings, DINet performs spa...

Image inpainting technique uses textural or structural information to repair or fill damaged potions of a picture. When dealing with a small area missing textural image, not only should guarantee the effectiveness of the algorithm, but the processing speed also need to be taken into account. In this paper, we propose a simply and effective inpainting method which combining fast inpainting metho...

We introduce a unified framework for the restoration of distorted audio data, leveraging the Image Inpainting concept and covering existing audio applications. In this framework, termed Audio Inpainting, the distorted data is considered missing and its location is assumed to be known. We further introduce baseline approaches based on sparse representations. For this new audio inpainting concept...

Inpainting methods play a vital role in various applications such as object removal, scratch removal, Image restoration. The filling-in missing region in an image is called image Inpainting. Time to time different algorithms came into existence for Inpainting missing region of an image. This paper introduces a novel framework for examplar based Inpainting. This paper presents a novel combinatio...

Inpainting refers to the task of filling in missing or damaged regions of an image. In this paper, we are interested in the inpainting problem where the missing regions are so large that local inpainting methods fail. As an alternative to the local principle, we make use of other images with related global information to enable a reasonable inpainting. Our method has roughly three phases: landm...

In this paper, we introduce fractional calculus into image inpainting and propose a new class of fractional-order variational image inpainting models, in both space and wavelet domains, inspired by the works of Bai and Feng. The corresponding Euler-Lagrange equations are given and proper numerical algorithm is analyzed. According to the simulations on several testing images, our algorithm demon...

Digital inpainting provides a means for reconstruction of small damaged portions of an image. Although the inpainting basics are straightforward, most inpainting techniques published in the literature are complex to understand and implement. We present here a new algorithm for digital inpainting based on the fast marching method for level set applications. Our algorithm is very simple to implem...