[2603.22279] 3D-Layout-R1: Structured Reasoning for Language-Instructed Spatial Editing

Computer Science > Computer Vision and Pattern Recognition arXiv:2603.22279 (cs) [Submitted on 23 Mar 2026] Title:3D-Layout-R1: Structured Reasoning for Language-Instructed Spatial Editing Authors:Haoyu Zhen, Xiaolong Li, Yilin Zhao, Han Zhang, Sifei Liu, Kaichun Mo, Chuang Gan, Subhashree Radhakrishnan View a PDF of the paper titled 3D-Layout-R1: Structured Reasoning for Language-Instructed Spatial Editing, by Haoyu Zhen and 7 other authors View PDF HTML (experimental) Abstract:Large Language Models (LLMs) and Vision Language Models (VLMs) have shown impressive reasoning abilities, yet they struggle with spatial understanding and layout consistency when performing fine-grained visual editing. We introduce a Structured Reasoning framework that performs text-conditioned spatial layout editing via scene-graph reasoning. Given an input scene graph and a natural-language instruction, the model reasons over the graph to generate an updated scene graph that satisfies the text condition while maintaining spatial coherence. By explicitly guiding the reasoning process through structured relational representations, our approach improves both interpretability and control over spatial relationships. We evaluate our method on a new text-guided layout editing benchmark encompassing sorting, spatial alignment, and room-editing tasks. Our training paradigm yields an average 15% improvement in IoU and 25% reduction in center-distance error compared to Chain of Thought Fine-tuning (CoT-SFT)...