HunyuanWorld 1.0 generates immersive 3D scenes from text and images using a semantically layered 3D mesh representation with panoramic world proxies, offering 360° experiences, mesh export, and disentangled object representations.
Creating immersive and playable 3D worlds from texts or images remains a
fundamental challenge in computer vision and graphics. Existing world
generation approaches typically fall into two categories: video-based methods
that offer rich diversity but lack 3D consistency and rendering efficiency, and
3D-based methods that provide geometric consistency but struggle with limited
training data and memory-inefficient representations. To address these
limitations, we present HunyuanWorld 1.0, a novel framework that combines the
best of both worlds for generating immersive, explorable, and interactive 3D
scenes from text and image conditions. Our approach features three key
advantages: 1) 360{\deg} immersive experiences via panoramic world proxies; 2)
mesh export capabilities for seamless compatibility with existing computer
graphics pipelines; 3) disentangled object representations for augmented
interactivity. The core of our framework is a semantically layered 3D mesh
representation that leverages panoramic images as 360{\deg} world proxies for
semantic-aware world decomposition and reconstruction, enabling the generation
of diverse 3D worlds. Extensive experiments demonstrate that our method
achieves state-of-the-art performance in generating coherent, explorable, and
interactive 3D worlds while enabling versatile applications in virtual reality,
physical simulation, game development, and interactive content creation.