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Point-cloud data collected in real-world applications are often incomplete.
Least-squares fitting of two 3-d point sets
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Convolutional occupancy networks
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J. Song, C. Meng, and S. Ermon · 2020
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R. Wu, X. Chen, Y. Zhuang, and B. Chen · 2020
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J. Tang · 2022
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Neural fields as learnable kernels for 3d reconstruction
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Text2tex: Text-driven texture synthesis via diffusion models
D. Z. Chen, Y. Siddiqui, H.-Y. Lee, S. Tulyakov, and M. Nießner · 2023
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Sdfusion: Multimodal 3d shape completion, reconstruction, and generation
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Diffusion-sdf: Text-to-shape via voxelized diffusion
M. Li, Y. Duan, J. Zhou, and J. Lu · 2023
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Realfusion: 360deg reconstruction of any object from a single image
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Latent-nerf for shape-guided generation of 3d shapes and textures
G. Metzer, E. Richardson, O. Patashnik, R. Giryes, and D. Cohen-Or · 2023
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Dreambooth3d: Subject-driven text-to-3d generation
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Texture: Text-guided texturing of 3d shapes
E. Richardson, G. Metzer, Y. Alaluf, R. Giryes, and D. Cohen-Or · 2023
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Make-it-3d: High-fidelity 3d creation from a single image with diffusion prior
J. Tang, T. Wang, B. Zhang, T. Zhang, R. Yi, L. Ma, and D. Chen · 2023
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