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Awesome GitHub RepositoriesDiffusion-Based 3D Guidance

The use of pre-trained 2D diffusion models as loss functions to guide the optimization of 3D shapes.

Distinct from Diffusion Models: Focuses on using diffusion as a guidance signal for 3D geometry rather than training 2D diffusion models.

Explore 1 awesome GitHub repository matching artificial intelligence & ml · Diffusion-Based 3D Guidance. Refine with filters or upvote what's useful.

Awesome Diffusion-Based 3D Guidance GitHub Repositories

Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
  • ashawkey/stable-dreamfusionAvatar ashawkey

    ashawkey/stable-dreamfusion

    8,841Vezi pe GitHub↗

    This project is a diffusion-based 3D generator and image-to-3D reconstruction system. It translates natural language descriptions or two-dimensional images into three-dimensional assets using neural radiance fields and diffusion models. The system utilizes score-distillation sampling and diffusion-based guidance to refine 3D shapes without requiring 3D training data. It includes specialized tools for transforming neural representations into exportable meshes with texture and material data, as well as a pipeline for iterative optimization of geometry and textures. The project covers a broad r

    Uses a pre-trained image generation model as a loss function to refine 3D shapes without 3D training data.

    Python
    Vezi pe GitHub↗8,841
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