Images 3Dmodel

--- license: mit pipeline_tag: image-to-3d --- # LGM Full # NLP to 3D Model – Custom Pipeline ## Overview This project showcases an experimental pipeline that bridges **natural language prompts to 3D model generation** using a modified version of a pre-trained multi-view diffusion model. It is part of a final year project for the *Comprehensive Creative Technologies Project* at UWE Bristol. The primary aim was to explore the potential of AI-assisted 3D content creation using natural language input. --- ## Model Source & Attribution This project **relies on the pre-trained model from the [LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation](https://huggingface.co/papers/2402.05054)**, developed for the **ML for 3D Course** by researchers at Google Research. 🔗 Original Model: *[https://huggingface.co/spaces/dylanebert/LGM-tiny]* 📄 Paper: [arXiv:2402.05054](https://arxiv.org/abs/2402.05054) 🔒 License: MIT I do not claim authorship of the model architecture or training process. This space serves as a **custom wrapper** for experimentation with **text-to-3D workflows**. --- ## What This Model Does - Allows input of a natural language description - Internally maps the input to a representative image or multi-view description - Generates a 3D model using the LGM pipeline --- ## Limitations - This is a prototype for academic use only. - The model’s ability to handle complex or abstract text is limited. - Performance and quality depend entirely on the base pre-trained model. --- ## Acknowledgements Thanks to Hugging Face and the authors of LGM for making their models publicly available. --- ## Author **Gordon CHIN HO AU** Final Year BSc Digital Media University of the West of England, Bristol

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