FurniMAS: Language-Guided Furniture Decoration using Multi-Agent System
This addresses the problem of time-consuming and expertise-dependent furniture decoration for industrial applications, though it appears incremental as it builds on multi-agent and LLM-based approaches.
The paper tackles automating furniture decoration by proposing FurniMAS, a multi-agent system that uses language prompts to suggest and arrange assets on furniture items, resulting in significantly outperforming baselines in generating high-quality 3D decor.
Furniture decoration is an important task in various industrial applications. However, achieving a high-quality decorative result is often time-consuming and requires specialized artistic expertise. To tackle these challenges, we explore how multi-agent systems can assist in automating the decoration process. We propose FurniMAS, a multi-agent system for automatic furniture decoration. Specifically, given a human prompt and a household furniture item such as a working desk or a TV stand, our system suggests relevant assets with appropriate styles and materials, and arranges them on the item, ensuring the decorative result meets functionality, aesthetic, and ambiance preferences. FurniMAS assembles a hybrid team of LLM-based and non-LLM agents, each fulfilling distinct roles in a typical decoration project. These agents collaborate through communication, logical reasoning, and validation to transform the requirements into the final outcome. Extensive experiments demonstrate that our FurniMAS significantly outperforms other baselines in generating high-quality 3D decor.