GenVDM: Generating Vector Displacement Maps From a Single Image
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912276348403712 |
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| author | Yang, Yuezhi Chen, Qimin Kim, Vladimir G. Chaudhuri, Siddhartha Huang, Qixing Chen, Zhiqin |
| author_facet | Yang, Yuezhi Chen, Qimin Kim, Vladimir G. Chaudhuri, Siddhartha Huang, Qixing Chen, Zhiqin |
| contents | We introduce the first method for generating Vector Displacement Maps (VDMs): parameterized, detailed geometric stamps commonly used in 3D modeling. Given a single input image, our method first generates multi-view normal maps and then reconstructs a VDM from the normals via a novel reconstruction pipeline. We also propose an efficient algorithm for extracting VDMs from 3D objects, and present the first academic VDM dataset. Compared to existing 3D generative models focusing on complete shapes, we focus on generating parts that can be seamlessly attached to shape surfaces. The method gives artists rich control over adding geometric details to a 3D shape. Experiments demonstrate that our approach outperforms existing baselines. Generating VDMs offers additional benefits, such as using 2D image editing to customize and refine 3D details. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_00605 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | GenVDM: Generating Vector Displacement Maps From a Single Image Yang, Yuezhi Chen, Qimin Kim, Vladimir G. Chaudhuri, Siddhartha Huang, Qixing Chen, Zhiqin Graphics Computer Vision and Pattern Recognition We introduce the first method for generating Vector Displacement Maps (VDMs): parameterized, detailed geometric stamps commonly used in 3D modeling. Given a single input image, our method first generates multi-view normal maps and then reconstructs a VDM from the normals via a novel reconstruction pipeline. We also propose an efficient algorithm for extracting VDMs from 3D objects, and present the first academic VDM dataset. Compared to existing 3D generative models focusing on complete shapes, we focus on generating parts that can be seamlessly attached to shape surfaces. The method gives artists rich control over adding geometric details to a 3D shape. Experiments demonstrate that our approach outperforms existing baselines. Generating VDMs offers additional benefits, such as using 2D image editing to customize and refine 3D details. |
| title | GenVDM: Generating Vector Displacement Maps From a Single Image |
| topic | Graphics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2503.00605 |