AIM 2019 Challenge on Image Demoireing: Dataset and Study
It addresses the problem of moire artifacts in images for computer vision researchers, but is incremental as it focuses on dataset creation and benchmarking.
The paper introduced the LCDMoire dataset of 10,200 synthetic image pairs for image demoireing and reviewed the AIM 2019 challenge results, summarizing the state-of-the-art on this dataset.
This paper introduces a novel dataset, called LCDMoire, which was created for the first-ever image demoireing challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ICCV 2019. The dataset comprises 10,200 synthetically generated image pairs (consisting of an image degraded by moire and a clean ground truth image). In addition to describing the dataset and its creation, this paper also reviews the challenge tracks, competition, and results, the latter summarizing the current state-of-the-art on this dataset.