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The idea of modeling object-object relations has been widely leveraged in many scene understanding applications. However, as the objects are designed by humans and for human usage, when we reason about a human environment, we reason about it through an interplay between the environment, objects and humans. In this paper, we model environments not only through objects, but also through latent human poses and human-object interactions. In order to handle the large number of latent human poses and a large variety of their interactions with objects, we present Infinite Latent Conditional Random Field (ILCRF) that models a scene as a mixture of CRFs generated from Dirichlet processes. In each CRF, we model objects and object-object relations as existing nodes and edges, and hidden human poses and human-object relations as latent nodes and edges. ILCRF generatively models the distribution of …