Intuitive explanation of how Latent SVM works?

Can anyone explain (or refer to a great explanation of) the intuition of how Latent SVM works?

I think Latent SVM should have some resemblance to CRF (Conditional Random Fields) and EM (expectation maximization) and of course standard SVM (max-margins, kernel trick) and I'll appreciate very much answers using these 'tools' to explain how Latent SVM works.