This content originally appeared on HackerNoon and was authored by Ringi
Table of Links
2. Related Works
2.1. 2D Diffusion Models for 3D Generation
2.2. 3D Generative Models and 2.3. Multi-view Diffusion Models
3. Problem Formulation
3.2. The Distribution of 3D Assets
4. Method and 4.1. Consistent Multi-view Generation
5. Experiments
5.4. Single View Reconstruction
5.5. Novel View Synthesis and 5.6. Discussions
6. Conclusions and Future Works, Acknowledgements and References
3.2. The Distribution of 3D Assets
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:::info This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license.
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:::info Authors:
(1) Xiaoxiao Long, The University of Hong Kong, VAST, MPI Informatik and Equal Contributions;
(2) Yuan-Chen Guo, Tsinghua University, VAST and Equal Contributions;
(3) Cheng Lin, The University of Hong Kong with Corresponding authors;
(4) Yuan Liu, The University of Hong Kong;
(5) Zhiyang Dou, The University of Hong Kong;
(6) Lingjie Liu, University of Pennsylvania;
(7) Yuexin Ma, Shanghai Tech University;
(8) Song-Hai Zhang, The University of Hong Kong;
(9) Marc Habermann, MPI Informatik;
(10) Christian Theobalt, MPI Informatik;
(11) Wenping Wang, Texas A&M University with Corresponding authors.
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This content originally appeared on HackerNoon and was authored by Ringi
Ringi | Sciencx (2025-01-01T20:00:14+00:00) Wonder3D: How We Distributed the 3D Assets. Retrieved from https://www.scien.cx/2025/01/01/wonder3d-how-we-distributed-the-3d-assets/
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