We achieve this goal using domain-invariant intermediate features, computed by the encoder part of our generator, and then projecting these features onto the domain-specific target distribution using the decoder. The translator network is “universal” because the number of parameters which need to be optimized should scale linearly with the number of domains. In more detail, our goal is to build and train a “universal” translator which can transform an image from an input domain to a target domain. We are the first to show how it can be effectively used in a MSDA setting. While this strategy has been recently adopted in the single-source UDA scenario , Then the synthetically generated images are usedįor training the target classifier. Specifically, we generate artificial target samplesīy “translating” images from all the source domains into target-like images. In this paper we deal with (unsupervised) MSDA using a data-augmentation approach based onĪ Generative Adversarial Network (GAN). We test our approach using common MSDA benchmarks, showing that it Way, new labeled images can be generated which are used to train a final targetĬlassifier. Representation onto the pixel space using the target domain and style. The dependence from the content is kept, and then re-project this invariant This reason we propose to project the image features onto a space where only (characterized in terms of low-level features variations) and the content. The appearance of a given image depends on three factors: the domain, the style Our method is inspired by the observation that
Propose the first approach for Multi-Source Domain Adaptation (MSDA) based on However, in practicalĪpplications, we typically have access to multiple sources. To the target domain from a single source dataset. Most domain adaptation methods consider the problem of transferring knowledge
I Take Offense to That Last One!: As Trigon starts chastising Raven some more after knocking out her friends, Raven gets angrier at the fact that he called her his father than her creator and master and that's when she gets her moment to literally and figuratively shine.Said comment lead to the defeat of the Evil Twins.
For Want of a Nail: Beast Boy made one off-hand comment.They eventually manage to defeat them by switching their opponents around. Evil Twin: Starfire, Cyborg, and Beast Boy are all fighting them.