# Compact Scene Graphs for Layout Composition and Patch Retrieval

## TL;DR

This paper introduces enhanced scene graph representations with heuristic relations and extreme points supervision, significantly improving scene composition and retrieval performance for complex scenes in image generation tasks.

## Contribution

It proposes novel enhancements to scene graph representations and a supervision method, leading to better scene composition and patch retrieval in complex scenes.

## Key findings

- Relation score improved from 51.2% to 69.0%.
- Enhanced scene graphs enable better rendering of cluttered scenes.
- Scene graphs facilitate retrieval of semantically similar image patches.

## Abstract

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.