HiFA: A New Text-to-3D Method With Advanced Diffusion Guidance

The model utilizes a novel training approach that "unlocks the potential of the diffusion prior".

Researchers Junzhe Zhu and Peiye Zhuang have introduced HiFA, a novel high-fidelity text-to-3D method with advanced diffusion guidance. The method utilizes the diffusion prior and a novel training approach to maximize the potential of the diffusion prior, enabling advanced photorealism and improved multi-view consistency. Additionally, the method applies auxiliary depth supervision for NeRF-rendered images and regularizes the density field of NeRFs, enhancing 3D geometry representation.

And here are some 3D meshes the team generated using the proposed method:

Prompt: A baby bunny sitting on top of a stack of pancakes

Prompt: A beautifully carved wooden knight chess piece

Prompt: A highly detailed stone bust of Theodoros Kolokotronis

Prompt: Small saguaro cactus planted in a clay pot

Prompt: Head of thanos

Prompt: Iron throne from game of thrones

Prompt: A ladybug

Prompt: A high pile of chocolate chip cookies

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