Diffusion-Based Signed Distance Fields for 3D Shape Generation
Jaehyeok Shim, Changwoo Kang, Kyungdon Joo
2023年份
28顶会引用
摘要
Figure 1. Visualization of 3D shape generation for various categories using SDF-Diffusion. SDF-diffusion gradually removes the Gaussian noise and generates high-resolution 3D shapes in the form of an SDF voxel by a two-stage framework. Unlike previous methods, which use point clouds, we can generate 3D meshes without concern of complex post-processing. For visualization purposes, we show less-noise data instead of the initial Gaussian noise.
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引用它的顶会 Paper28
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它引用的顶会 Paper39
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