Abstract: Procedural Content Generation (PCG) is powerful in creating high-quality 3D contents, yet controlling it to produce desired shapes is difficult and often requires extensive parameter tuning.
Practical workflows using Unity-MCP's 71 tools, 46 prompts, and 1 resource. All examples show what you can ask your AI client to do once Unity-MCP is connected. "Create a new scene called 'Level01', ...
This repository contains code release for our CVPR 2025 paper "DI-PCG: Diffusion-based Efficient Inverse Procedural Content Generation for High-quality 3D Asset Creation". conda create -n di-pcg ...
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