MSGAN
Multi-source Sentiment Generative Adversarial Network
**Multi-source Sentiment Generative Adversarial Network** is a multi-source domain adaptation (MDA) method for visual sentiment classification. It is composed of three pipelines, i.e., image reconstruction, image translation, and cycle-reconstruction. To handle data from multiple source domains, it learns to find a unified sentiment latent space where data from both the source and target domains share a similar distribution. This is achieved via cycle consistent adversarial learning in an end-to-end manner. Notably, thanks to the unified sentiment latent space, MSGAN requires a single classification network to handle data from different source domains.
Multi-source Domain Adaptation for Visual Sentiment Classification
https://paperswithcode.com/paper/multi-source-domain-adaptation-for-visual
Multi-source Domain Adaptation for Visual Sentiment Classification