We propose an end-to-end variational generative model for scene layout
synthesis conditioned on scene graphs. Unlike unconditional scene layout
generation, we use scene graphs as an abstract but general representation to
guide the synthesis of diverse scene layouts that satisfy relationships
included in the scene graph. This gives rise to more flexible control over the
synthesis process, allowing various forms of inputs such as scene layouts
extracted from sentences or inferred from a single color image. Using our
conditional layout synthesizer, we can generate various layouts that share the
same structure of the input example. In addition to this conditional generation
design, we also integrate a differentiable rendering module that enables layout
refinement using only 2D projections of the scene. Given a depth and a
semantics map, the differentiable rendering module enables optimizing over the
synthesized layout to fit the given input in an analysis-by-synthesis fashion.
Experiments suggest that our model achieves higher accuracy and diversity in
conditional scene synthesis and allows exemplar-based scene generation from
various input forms.

提出一种基于变分生成模型和场景图条件的端到端场景布局合成方法，并使用可微分渲染模块优化生成的布局。实验表明，该模型可以更精确和多样地进行条件场景合成，并允许从各种输入形式生成样本化场景。