Text2Immersion: Generative Immersive Scene with 3D Gaussians
Hao Ouyang Kathryn Heal Stephen Lombardi Tiancheng Sun
We introduce Text2Immersion, an elegant method for producing high-quality 3D
immersive scenes from text prompts. Our proposed pipeline initiates by
progressively generating a Gaussian cloud using pre-trained 2D diffusion and
depth estimation models. This is followed by a refining stage on the Gaussian
cloud, interpolating and refining it to enhance the details of the generated
scene. Distinct from prevalent methods that focus on single object or indoor
scenes, or employ zoom-out trajectories, our approach generates diverse scenes
with various objects, even extending to the creation of imaginary scenes.
Consequently, Text2Immersion can have wide-ranging implications for various
applications such as virtual reality, game development, and automated content
creation. Extensive evaluations demonstrate that our system surpasses other
methods in rendering quality and diversity, further progressing towards
text-driven 3D scene generation. We will make the source code publicly
accessible at the project page.