2015
NeurIPS
NeurIPS 2015
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.
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Interdisciplinary Bridge
- Artificial Intelligence and Computer Vision
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Trend Setter
- Visual Question Answering
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Hot Topic Early Bird
- siamese network
Authors
Topics
Machine Learning > Core Methods > Metric Learning
Machine Learning > Core Methods > Embedding Learning
Computer Vision > Analysis > Scene Understanding
Computer Vision > Core AI > Computer Vision
Deep Learning > Learning Types > Metric Learning
Deep Learning > Architectures > Convolutional Neural Networks
Computer Vision > Applications > Visual Question Answering