Webaverse

Stable-Dreamfusion

Webaverse

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The Stable-Dreamfusion is a PyTorch implementation of the text-to-3D model Dreamfusion, powered by the Stable Diffusion text-to-2D model. It uses the multi-resolution grid encoder to implement the NeRF backbone, enabling much faster rendering compared to the original Dreamfusion paper. However, the current generation quality cannot match the results from the original paper, and many prompts still fail badly. Model inputs and outputs Inputs Text prompts**: The model takes text prompts as input to generate 3D content. Outputs 3D Renders**: The model outputs 3D renders of the scene described in the text prompt, which can be viewed in real-time using the provided GUI. Capabilities The Stable-Dreamfusion model can generate 3D content from text prompts, such as "a high quality photo of a pineapple". However, the current implementation has limitations and the quality does not yet match the original Dreamfusion paper. What can I use it for? The Stable-Dreamfusion model is a work-in-progress and intended for research purposes only. Potential use cases include generating 3D art and models, as well as exploring the limitations and biases of text-to-3D generation models. However, the model should not be used for any malicious or harmful purposes. Things to try Researchers and developers can experiment with the Stable-Dreamfusion model to better understand the challenges of text-to-3D generation, such as the "Janus problem" of multiple faces. They can also explore ways to improve the surface quality of the generated 3D meshes.

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