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 …

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 …

Deep image completion usually fails to harmonically blend the restored image into existing
content, especially in the boundary area. This paper handles this problem from a new …

Bridging global context interactions correctly is important for high-fidelity image completion
with large masks. Previous methods attempting this via deep or large receptive field (RF) …

Most image completion methods produce only one result for each masked input, although
there may be many reasonable possibilities. In this paper, we present an approach for …

Image completion has made tremendous progress with convolutional neural networks
(CNNs), because of their powerful texture modeling capacity. However, due to some …

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 …

Recent advances in generative imagery have brought forth outpainting and inpainting
models that can produce high-quality, plausible image content in unknown regions, but the …

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 …