Research map / Vision-language and multimodal / Multimodal LLMs
3D Space as a Scratchpad for Editable Text-to-Image Generation
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Proposes a 3D spatial scratchpad in which an LLM agent pipeline parses a prompt, instantiates subjects as image-to-3D meshes, plans placement, orientation and camera in 3D, and renders the scene as depth plus identity conditioning for SIGMA-Gen image generation, enabling editable text-to-image generation without additional training.
Problem
Text-to-image generators and VLMs struggle with precise spatial relations, object identity consistency and compositional coherence for complex prompts, and 2D layout-based planning is limited for spatial reasoning.
Approach
Use an explicit editable 3D scene (meshes placed by LLM agents) as an intermediate reasoning workspace, rendered back to depth and identity-conditioned image generation, so 3D edits propagate to the final image while preserving subject identity.
Key results
- On GenAI-Bench, the method reaches 0.83 text alignment versus 0.63 for Flux.1 [dev] and 0.80 for Idea2Img, with image quality 4.81.
- On CompoundPrompts, text alignment is 0.91 versus 0.85 for Flux and 0.87 for Idea2Img.
- On T2I-CompBench, 3D spatial score is 0.54 versus 0.43 for RPG-Flux and 0.39 for Flux.
Surprising findings
- Providing the LLM with renders of the scene and asking for transformation matrices directly fails, and using full generated images for orientation estimation is unreliable.
- Adding rulers to scratchpad renders improves text alignment on GenAI-Bench.
Limitations
- LLM-generated 3D arrangements can be too uniform and not reflect real-world compositions.
- Generated meshes have limited pose diversity and articulated assets cannot be reposed.
- Activity and orientation understanding may fail in complex interactions.
Experimental setup
Datasets: GenAI-Bench CompoundPrompts T2I-CompBench
Benchmarks: GenAI-Bench CompoundPrompts T2I-CompBench
Metrics: VQAScore Q-Align UniDet-based spatial score 3-in-1 metric
Baselines: Flux.1 [dev] Idea2Img RPG - SDXL RPG - Flux Iterative Insert-Anything DALL-E-3
Builds on: SIGMA-Gen Idea2Img RPG Hunyuan-3D 2.5 Flux.1 [dev]
Closest papers by meaning
- Let Language Constrain Geometry: Vision–Language Models as Semantic and Spatial Critics for 3D Generation (ICML 2026 · similarity 0.89)
- LayoutVLM: Differentiable Optimization of 3D Layout via Vision-Language Models (CVPR 2025 · similarity 0.89)
- Socratic-Geo: Synthetic Data Generation and Cross-Modal Geometric Reasoning via Multi-Agent Interaction (CVPR 2026 · similarity 0.88)
- Reinforcing Spatial Reasoning in Vision-Language Models with Interwoven Thinking and Visual Drawing (NeurIPS 2025 · similarity 0.88)
- Think with 3D: Geometric Imagination Grounded Spatial Reasoning from Limited Views (CVPR 2026 · similarity 0.88)
- Think, Plan, Paint: Layout-Aware Reasoning for Controllable Image Generation in Unified Models (NeurIPS 2026 · similarity 0.88)
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