  Text-driven 3D indoor scene generation holds broad applications, ranging from
gaming and smart homes to AR/VR applications. Fast and high-fidelity scene
generation is paramount for ensuring user-friendly experiences. However,
existing methods are characterized by lengthy generation processes or
necessitate the intricate manual specification of motion parameters, which
introduces inconvenience for users. Furthermore, these methods often rely on
narrow-field viewpoint iterative generations, compromising global consistency
and overall scene quality. To address these issues, we propose FastScene, a
framework for fast and higher-quality 3D scene generation, while maintaining
the scene consistency. Specifically, given a text prompt, we generate a
panorama and estimate its depth, since the panorama encompasses information
about the entire scene and exhibits explicit geometric constraints. To obtain
high-quality novel views, we introduce the Coarse View Synthesis (CVS) and
Progressive Novel View Inpainting (PNVI) strategies, ensuring both scene
consistency and view quality. Subsequently, we utilize Multi-View Projection
(MVP) to form perspective views, and apply 3D Gaussian Splatting (3DGS) for
scene reconstruction. Comprehensive experiments demonstrate FastScene surpasses
other methods in both generation speed and quality with better scene
consistency. Notably, guided only by a text prompt, FastScene can generate a 3D
scene within a mere 15 minutes, which is at least one hour faster than
state-of-the-art methods, making it a paradigm for user-friendly scene
generation.
