SOURCE-LINKED INTELLIGENCE
ScenePilot: Grow-and-Repair Policy for Text-Driven 3D Indoor Scene Generation
Text-driven 3D indoor scene generation has advanced from dataset-bound layout modeling to open-vocabulary synthesis with large language and vision-language models. Yet existing methods remain limited: one-pass generators often yield geometrically invalid layouts, heavy post-hoc optimization is costly and unstable, and prompt-only planners lack reusable layout priors for functional grouping and object relations. We propose \textbf{ScenePilot}, a retrieval-augmented \textbf{Grow-and-Repair} framework that formulates scene generation as prior-guided incremental growth with learned rectification.
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-31T06:22:11.000Z
First collected: 2026-09-21T07:22:03.933Z. This is not the publication date.