Seam carving is a method to resize an image in a content aware fashion. However, this method can also be used to carve out objects from images. In this paper, we propose a two-step method to detect and localize seam carved images. First, we build a detector to detect small patches in an image that has been seam carved. Next, we compute a heatmap on an image based on the patch detector's output. Using these heatmaps, we build another detector to detect if a whole image is seam carved or not. Our experimental results show that our approach is effective in detecting and localizing seam carved images.
@article{arxiv.2109.01764,
title = {Seam Carving Detection and Localization using Two-Stage Deep Neural Networks},
author = {Lakshmanan Nataraj and Chandrakanth Gudavalli and Tajuddin Manhar Mohammed and Shivkumar Chandrasekaran and B. S. Manjunath},
journal= {arXiv preprint arXiv:2109.01764},
year = {2021}
}