A Study on the Next-Generation 3D Modeling Pipeline through the Integration of Generative AI and Photogrammetry
3
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
This study proposes and verifies a next-generation 3D modeling pipeline integrating Generative AI and Photogrammetry techniques. Two types of objects were selected for experimentation: a bust combining characteristics of both objects and characters, and a stone slab exhibiting planar and symmetrical features. Firstly, videos depicting these objects from various viewpoints were generated using generative AI models. Secondly, these videos were processed through Photogrammetry software to produce high-quality 3D meshes and diffuse textures. Lastly, post-processing including high and Low-polygon mesh separation, UV unwrapping, and texture baking was performed, successfully producing Physically Based Rendering (PBR)-compatible game assets. The proposed pipeline demonstrates significant potential for practical applications across various industries, and further advances in generative AI and future research are expected to broaden this novel approach to digital asset creation.
Abstract
This study proposes and verifies a next-generation 3D modeling pipeline integrating Generative AI and Photogrammetry techniques. Two types of objects were selected for experimentation: a bust combining characteristics of both objects and characters, and a stone slab exhibiting planar and symmetrical features. Firstly, videos depicting these objects from various viewpoints were generated using generative AI models. Secondly, these videos were processed through Photogrammetry software to produce high-quality 3D meshes and diffuse textures. Lastly, post-processing including high and Low-polygon mesh separation, UV unwrapping, and texture baking was performed, successfully producing Physically Based Rendering (PBR)-compatible game assets. The proposed pipeline demonstrates significant potential for practical applications across various industries, and further advances in generative AI and future research are expected to broaden this novel approach to digital asset creation.