The Elephant in the Room
Computer Vision and Pattern Recognition
2018-08-13 v1 Machine Learning
Abstract
We showcase a family of common failures of state-of-the art object detectors. These are obtained by replacing image sub-regions by another sub-image that contains a trained object. We call this "object transplanting". Modifying an image in this manner is shown to have a non-local impact on object detection. Slight changes in object position can affect its identity according to an object detector as well as that of other objects in the image. We provide some analysis and suggest possible reasons for the reported phenomena.
Keywords
Cite
@article{arxiv.1808.03305,
title = {The Elephant in the Room},
author = {Amir Rosenfeld and Richard Zemel and John K. Tsotsos},
journal= {arXiv preprint arXiv:1808.03305},
year = {2018}
}