WorldAgents: Can Foundation Image Models be Agents for 3D World Models?

Given the remarkable ability of 2D foundation image modelsto generate high-fidelity outputs, we investigate a fundamental question:do 2D foundation image models inherently possess 3D world model ca-pabilities? To answer this, we systematically evaluate multiple state-of-the-art image generation models and Vision-Language Models (VLMs)on the task of 3D world synthesis. To harness and benchmark their po-tential implicit 3D capability, we propose an agentic framing to facilitate3D world generation. Our approach employs a multi-agent architecture:a VLM-based director that formulates prompts to guide image synthesis,a generator that synthesizes new image views, and a VLM-backed two-step verifier that evaluates and selectively curates generated frames fromboth 2D image and 3D reconstruction space. Crucially, we demonstratethat our agentic approach provides coherent and robust 3D reconstruc-tion, producing output scenes that can be explored by rendering novelviews. Through extensive experiments across various foundation mod-els, we demonstrate that 2D models do indeed encapsulate a grasp of3D worlds. By exploiting this understanding, our method successfullysynthesizes expansive, realistic, and 3D-consistent worlds.