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Model card for InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models.
Source du modèle
Description de la source
Model card for InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models.
Code: https://github.com/TencentARC/InstantMesh
Arxiv: https://arxiv.org/abs/2404.07191
We present InstantMesh, a feed-forward framework for instant 3D mesh generation from a single image, featuring state-of-the-art generation quality and significant training scalability. By synergizing the strengths of an off-the-shelf multiview diffusion model and a sparse-view reconstruction model based on the LRM architecture, InstantMesh is able to create diverse 3D assets within 10 seconds. To enhance the training efficiency and exploit more geometric supervisions, e.g., depths and normals, we integrate a differentiable iso-surface extraction module into our framework and directly optimize on the mesh representation. Experimental results on public datasets demonstrate that InstantMesh significantly outperforms other latest image-to-3D baselines, both qualitatively and quantitatively. We release all the code, weights, and demo of InstantMesh, with the intention that it can make substantial contributions to the community of 3D generative AI and empower both researchers and content creators.
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1 sourceVérifié 8 sept.
Artefacts du modèle
5 artefactsExtraits de sources
2 extraitsinstant_mesh_large.ckpt
ckpt · 1,41 GB · SHA-256 329f7aae9b58…91a1 · Hugging Face
--- license: apache-2.0 tags: - image-to-3d --- # InstantMesh Model card for *InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models*. Code: https://github.com/TencentARC/InstantMesh Arxiv: https://arxiv.org/abs/2404.07191 We present InstantMesh, a feed-forward framework for instant 3D mesh generation from a single image, featuring state-of-the-art generation quality and significant training scalability. By synergizing the strengths of an off-the-shelf multiview diffusion model and a sparse-view reconstruction model based on the LRM architecture, InstantMesh is able to create diverse 3D assets within 10 seconds. To enhance the training efficiency and exploit more geometric supervisions, e.g., depths and normals, we integrate a differentiable iso-surface extraction module into our framework and directly optimize on the mesh representation. Experimental results on public datasets demonstrate that InstantMesh significantly outperforms other latest image-to-3D baselines, both qualitatively and quantitatively. We release all the code, weights, and demo of InstantMesh, with the intention that it can make substantial contributions to the community of 3D generative AI and empower both researchers and content creators.
Source context: 15380 downloads · 340 likes · Pipeline image-to-3d · Library diffusers · Repo TencentARC/InstantMesh
