Structured representations such as scene graphs serve as an efficient and
compact representation that can be used for downstream rendering or retrieval
tasks. However, existing efforts to generate realistic images from scene graphs
perform poorly on scene composition for cluttered or complex scenes. We propose
two contributions to improve the scene composition. First, we enhance the scene
graph representation with heuristic-based relations, which add minimal storage
overhead. Second, we use extreme points representation to supervise the
learning of the scene composition network. These methods achieve significantly
higher performance over existing work (69.0% vs 51.2% in relation score
metric). We additionally demonstrate how scene graphs can be used to retrieve
pose-constrained image patches that are semantically similar to the source
query. Improving structured scene graph representations for rendering or
retrieval is an important step towards realistic image generation.

提出了两种改进场景结构表示法的方法，通过启发式关系和极端点表示法，显著提高相关分数测量方法的性能，并演示了如何使用场景图检索与源查询语义相似的姿态约束图像块，这是实现逼真图像生成的重要一步。