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.