Visalogy: Answering Visual Analogy Questions
Abstract
In this paper, we study the problem of answering visual analogy questions. These questions take the form of image A is to image B as image C is to what. Answering these questions entails discovering the mapping from image A to image B and then extending the mapping to image C and searching for the image D such that the relation from A to B holds for C to D. We pose this problem as learning an embedding that encourages pairs of analogous images with similar transformations to be close together using convolutional neural networks with a quadruple Siamese architecture. We introduce a dataset of visual analogy questions in natural images, and show first results of its kind on solving analogy questions on natural images.
Cite
Text
Sadeghi et al. "Visalogy: Answering Visual Analogy Questions." Neural Information Processing Systems, 2015.Markdown
[Sadeghi et al. "Visalogy: Answering Visual Analogy Questions." Neural Information Processing Systems, 2015.](https://mlanthology.org/neurips/2015/sadeghi2015neurips-visalogy/)BibTeX
@inproceedings{sadeghi2015neurips-visalogy,
title = {{Visalogy: Answering Visual Analogy Questions}},
author = {Sadeghi, Fereshteh and Zitnick, C. Lawrence and Farhadi, Ali},
booktitle = {Neural Information Processing Systems},
year = {2015},
pages = {1882-1890},
url = {https://mlanthology.org/neurips/2015/sadeghi2015neurips-visalogy/}
}