mlsanityData to 14 Oct 2026

DesignAgent3D: Interactive 3D Scene Editing via Designer-like Multimodal Reasoning

arXiv 2608.21438 ↗First posted 18 Aug 2026cs.CV cs.MAcited by 0

On the map: LLM reasoning → Spatial and embodied reasoning

Abstract (arXiv)

Text guided 3D scene editing provides an intuitive interface for modifying reconstructed environments, but remains difficult because natural language design requests are often semantically underspecified and must be grounded in cluttered 3D scenes. Existing methods typically formulate the task as one-shot conditional generation from a single prompt, failing to resolve ambiguous user intents or achieve precise spatial grounding. Consequently, they suffer from severe object localization drift, tracking failure under occlusions, and the notorious multi-view "sticker effect." To overcome these limitations, we present DesignAgent3D, an interactive multimodal agentic framework that reformulates 3D scene editing as a designer-like Plan-Perceive-Act paradigm. The agent first plans by interacting with the user to clarify underspecified design goals, then perceives by grounding the intended edit to specific objects or regions in the 3D scene, and finally acts by applying controlled visual modifications while preserving scene consistency. The edits are further integrated into the underlying 3D representation, supporting persistent and multi-view consistent novel-view rendering. Extensive experiments across both NeRF and 3D Gaussian Splatting backbones demonstrate that DesignAgent3D significantly outperforms state-of-the-art baselines, delivering superior semantic intent alignment, impeccable spatial localization accuracy, and high-fidelity multi-view consistency.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Spatial and embodied reasoning, one of 17 directions in LLM reasoning. Builds on 5 of its 27 references that are in the map. First posted on arXiv 18 Aug 2026.

Builds on

5 of 27 references.

References · 5

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,356
  3. 2019The Replica Dataset: A Digital Replica of Indoor Spacescited by 904
  4. 2023Gemini: A Family of Highly Capable Multimodal Modelscited by 872
  5. 2023An Embodied Generalist Agent in 3D Worldcited by 365

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  1. 2026ViSculpt: Visual-Centric Agentic Geometry Editing
  2. 2025Scenethesis: A Language and Vision Agentic Framework for 3D Scene Generation
  3. 2026MUSE: Agentic 3D Scene Authoring via Memory-Grounded Incremental Requirement Satisfaction
  4. 2026Vinedresser3D: Agentic Text-guided 3D Editing
  5. 2026SimWorlds: A Multi-Agent System for Dynamic 3D Scene Creation
  6. 2025SceneWeaver: All-in-One 3D Scene Synthesis with an Extensible and Self-Reflective Agent
  7. 2026SceneOrchestra: Efficient Agentic 3D Scene Synthesis via Full Tool-Call Trajectory Generation
  8. 2025VULCAN: Tool-Augmented Multi Agents for Iterative 3D Object Arrangement