| --- |
| pipeline_tag: depth-estimation |
| library_name: diffusers |
| --- |
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| # GeoNeXt |
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| **Video Generative Models as Geometry Learner** |
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| GeoNeXt is a unified framework for monocular depth and surface normal estimation, repurposing pretrained video generative models for geometry prediction through a next-frames formulation. |
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| - **Paper**: [Video Generative Models as Geometry Learner](https://huggingface.co/papers/2608.28549) |
| - **Project page**: [https://happy-hsy.github.io/projects/GeoNeXt/](https://happy-hsy.github.io/projects/GeoNeXt/) |
| - **GitHub**: [https://github.com/Creative-Intelligence-Studio/GeoNeXt](https://github.com/Creative-Intelligence-Studio/GeoNeXt) |
| - **Model checkpoints**: [happy0612/GeoNeXt](https://huggingface.co/happy0612/GeoNeXt) |
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| The repository contains checkpoints for GeoNeXt-Wan and GeoNeXt-SVD. Follow the instructions in the GitHub repository to run inference for depth and normal estimation. |
