This paper develops a unified framework for image-to-image translation based on
conditional diffusion models and evaluates this framework on four challenging image-to …

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 …

We propose a method for automatically guiding patch-based image completion using mid-
level structural cues. Our method first estimates planar projection parameters, softly …

This paper surveys the state-of-the-art of research in patch-based synthesis. Patch-based
methods synthesize output images by copying small regions from exemplar imagery. This …

Image outpainting seeks for a semantically consistent extension of the input image beyond
its available content. Compared to inpainting---filling in missing pixels in a way coherent with …

We present a novel method for aligning images in an HDR (high-dynamic-range) image
stack to produce a new exposure stack where all the images are aligned and appear as if …

This paper studies the fundamental problem of extrapolating visual context using deep
generative models, ie, extending image borders with plausible structure and details. This …

Image extension models have broad applications in image editing, computational
photography and computer graphics. While image inpainting has been extensively studied …

Blind inpainting is a task to automatically complete visual contents without specifying masks
for missing areas in an image. Previous work assumes known missing-region-pattern …

Comparing to image inpainting, image outpainting receives less attention due to two
challenges in it. The first challenge is how to keep the spatial and content consistency …