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Recent advancements in open-world 3D object generation have been remarkable,with image-to-3D methods offering superior fine-grained control over theirtext-to-3D counterparts. However, most existing models fall short insimultaneously providing rapid generation speeds and high fidelity to inputimages - two features essential for practical applications. In this paper, wepresent One-2-3-45++, an innovative method that transforms a single image intoa detailed 3D textured mesh in approximately one minute. Our approach aims tofully harness the extensive knowledge embedded in 2D diffusion models andpriors from valuable yet limited 3D data. This is achieved by initiallyfinetuning a 2D diffusion model for consistent multi-view image generation,followed by elevating these images to 3D with the aid of multi-view conditioned3D native diffusion models. Extensive experimental evaluations demonstrate thatour method can produce high-quality, diverse 3D assets that closely mirror theoriginal input image. Our project webpage:https://sudo-ai-3d.github.io/One2345plus_page.

One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View Generation and 3D Diffusion