GeoWorld: Providing Full-frame Geometry Features to Facilitate 3D Scene Generation
Abstract
A two-stage method for image-to-3D scene generation that uses full-frame geometry features and geometric constraints to improve fidelity and speed over existing approaches.
Previous works that leverage video models for image-to-3D scene generation often suffer from geometric distortions and blurry content. Using video generation models to implicitly maintain geometric consistency according to a single-frame input is ineffective. In this paper, we present a two-stage method, named GeoWorld, that renovates the image-to-3D scene generation pipeline by providing full-frame geometry features. The first-stage video generation model, followed by a multi-view geometry model, produces full-frame geometry features, which are then used as a mental draft of geometric conditions to aid the second-stage video-generation model. A geometric loss is proposed to impose real-world geometric constraints, and a geometry adaptation module is introduced to ensure the effective utilization of geometry features. Thanks to full-frame geometric modeling, the two smaller video models in our two-stage method can generate higher-fidelity 3D scenes than SOTA methods, while being even faster, e.g. 7.5times faster than Hunyuan-Voyager. Project page: https://peaes.github.io/GeoWorld.
Community
We are happy to release the project page, code, and model for GeoWorld: Providing Full-frame Geometry Features to Facilitate 3D Scene Generation.
Code: https://github.com/peaes/GeoWorld
Project Page: https://peaes.github.io/GeoWorld
Model: https://huggingface.co/peaes/GeoWorld
Thanks for your interest!
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