  Object placement aims to place a foreground object over a background image
with a suitable location and size. In this work, we treat object placement as a
graph completion problem and propose a novel graph completion module (GCM). The
background scene is represented by a graph with multiple nodes at different
spatial locations with various receptive fields. The foreground object is
encoded as a special node that should be inserted at a reasonable place in this
graph. We also design a dual-path framework upon the structure of GCM to fully
exploit annotated composite images. With extensive experiments on OPA dataset,
our method proves to significantly outperform existing methods in generating
plausible object placement without loss of diversity.
