Learning Visual Context by Comparison [article]

Minchul Kim, Jongchan Park, Seil Na, Chang Min Park, Donggeun Yoo
2020 arXiv   pre-print
Finding diseases from an X-ray image is an important yet highly challenging task. Current methods for solving this task exploit various characteristics of the chest X-ray image, but one of the most important characteristics is still missing: the necessity of comparison between related regions in an image. In this paper, we present Attend-and-Compare Module (ACM) for capturing the difference between an object of interest and its corresponding context. We show that explicit difference modeling
more » ... be very helpful in tasks that require direct comparison between locations from afar. This module can be plugged into existing deep learning models. For evaluation, we apply our module to three chest X-ray recognition tasks and COCO object detection & segmentation tasks and observe consistent improvements across tasks. The code is available at https://github.com/mk-minchul/attend-and-compare.
arXiv:2007.07506v1 fatcat:mhwvyzjvm5edzlrzkueg4yepiy