LEGO-Anything: Coding Agents for 3D Scene Reconstruction

arXiv:2609.36380 · cs.CV · Submitted 2026-09-28 · Read on arXiv

cs.CV

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/ahujasid/blender-mcp

Project page: https://lego-anything.com

Terminology

• Benchmark — 40× in this paper · explained in 2 episodes
• Fidelity — 12× in this paper · explained in 2 episodes
• Alignment — 8× in this paper · explained in 1 episode
• Verifier — 7× in this paper · explained in 2 episodes
• Aggregation — 6× in this paper · explained in 1 episode
• Benchmarking — 5× in this paper · explained in 3 episodes
• Regret — 5× in this paper · explained in 3 episodes
• Verification — 4× in this paper · explained in 2 episodes
• Actor — 3× in this paper · explained in 3 episodes
• Instance Segmentation — 3× in this paper · explained in 3 episodes
• Action Space — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Digital Twin — 2× in this paper · explained in 4 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Human-in-the-Loop — 2× in this paper · explained in 3 episodes
• Test-time Scaling — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Agent Harness — 1× in this paper · explained in 2 episodes
• Agentic Coding — 1× in this paper · explained in 1 episode
• Agentic Discovery — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Structural Reasoning — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• Gen3DSR: Generalizable 3D Scene Reconstruction via Divide and Conquer from a Single View
• PhysX-Anything: Simulation-Ready Physical 3D Assets from Single Image
• Collaborative Multi-Modal Coding for High-Quality 3D Generation
• SAM 3: Segment Anything with Concepts
• Sandboxed Coding Agents are Competitive Omni-modal Task Solvers
• BlenderFusion: 3D-Grounded Visual Editing and Generative Compositing
• Panoptic 3D Scene Reconstruction From a Single RGB Image
• ProcTHOR: Large-Scale Embodied AI Using Procedural Generation
• CityCraft: A Real Crafter for 3D City Generation
• CaP-X: A Framework for Benchmarking and Improving Coding Agents for Robot Manipulation
• 3DCodeBench: Benchmarking Agentic Procedural 3D Modeling Via Code
• Mesh R-CNN
• LVIS: A Dataset for Large Vocabulary Instance Segmentation
• Thinking in Blender: Staged Executable Inverse Graphics with Vision-Language Models
• SceneCraft: An LLM Agent for Synthesizing 3D Scene as Blender Code
• LiteReality: Graphics-Ready 3D Scene Reconstruction from RGB-D Scans
• Ditto: Building Digital Twins of Articulated Objects from Interaction
• SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
• SimWorld Studio: Automatic Environment Generation with Evolving Coding Agent for Embodied Agent Learning
• SceneConductor: 3D Scene Generation from a Single Image with Multi-Agent Orchestration

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