Imperative vs. Declarative Programming Paradigms for Open-Universe Scene Generation

Synthesizing 3D scenes from open-vocabulary text descriptions is a challenging, important, and recently-popular application. One of its critical subproblems is layout generation: given a set of objects, lay them out to produce a scene matching the input description. Nearly all recent work adopts a declarative paradigm for this problem: using LLM to generate specification of constraints between objects, then solving those constraints to produce the final layout. In contrast, we explore an alternative imperative paradigm, in which an LLM iteratively places objects, with each object's position and orientation computed as a function of previously-placed objects. The imperative approach allows for a simpler scene specification language while also handling a wider variety and larger complexity of scenes. We further improve the robustness of our imperative scheme by developing an error correction mechanism that iteratively improves the scene's validity while staying as close as possible the original layout generated by the LLM. In forced-choice perceptual studies, participants preferred layouts generated by our imperative approach 82% and 94% of the time, respectively, when compared against two declarative layout generation methods. We also present a simple, automated evaluation metric for 3D scene layout generation that aligns well with human preferences.

@article{gumin2025_2504.05482,
  title={ Imperative vs. Declarative Programming Paradigms for Open-Universe Scene Generation },
  author={ Maxim Gumin and Do Heon Han and Seung Jean Yoo and Aditya Ganeshan and R. Kenny Jones and Rio Aguina-Kang and Stewart Morris and Daniel Ritchie },
  journal={arXiv preprint arXiv:2504.05482},
  year={ 2025 }
}