We present a new method for completing missing parts caused by the removal of foreground
or background elements from an image. Our goal is to synthesize a complete, visually …

We present a novel approach for image completion that results in images that are both
locally and globally consistent. With a fully-convolutional neural network, we can complete …

What can you do with a million images? In this paper we present a new image completion
algorithm powered by a huge database of photographs gathered from the Web. The …

This paper presents a novel gradient-based image completion algorithm for removing
significant objects from natural images or photographs. Our method reconstructs the region …

What can you do with a million images? In this paper, we present a new image completion
algorithm powered by a huge database of photographs gathered from the Web. The …

We present a data-driven method to predict the quality of an image completion method. Our
method is based on the state-of-the-art non-parametric framework of Wexler et al.[2007]. It …

Image completion involves filling missing parts in images. In this paper we address this
problem through the statistics of patch offsets. We observe that if we match similar patches in …

Image completion involves filling missing parts in images. In this paper we address this
problem through novel statistics of similar patches. We observe that if we match similar …

Video completion is the problem of automatically filling space–time holes in video
sequences left by the removal of unwanted objects in a scene. We solve it using texture …

In this paper, we introduce a novel approach to image completion, which we call structure
propagation. In our system, the user manually specifies important missing structure …