Using post-production software to place things realistically in scenes is much tougher for computers than for humans. It requires not only determining an appropriate location for said object, but trying to predict the object's appearance at the target location -- its scale, occlusions, pose, shape, and more. Fortunately, artificial intelligence (AI) promises to lend a hand. In a paper accepted at the NeurIPS 2018 conference last week ("Context-Aware Synthesis and Placement of Object Instances"), researchers at Seoul National University, the University of California at Merced, and Google AI describe a system that learns to insert an object into an image in a "semantically coherent" -- that is to say, convincing -- manner. "Inserting objects into an image that conforms to scene semantics is a challenging and interesting task. The task is closely related to many real-world applications, including image synthesis, AR and VR content editing and domain randomization," the researchers wrote.