2017

Generate To Adapt: Aligning Domains using Generative Adversarial Networks

Sankaranarayanan, Swami, Balaji, Yogesh, Castillo, Carlos D. et al.

Understand

Domain Adaptation is an actively researched problem in Computer Vision.

In this work, we propose an approach that leverages unsupervised data to bring the source and target distributions closer in a learned joint feature space.
We accomplish this by inducing a symbiotic relationship between the learned embedding and a generative adversarial network.
This is in contrast to methods which use the adversarial framework for realistic data generation and retraining deep models with such data.

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Then

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