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Edify 3D: Scalable High-Quality 3D Asset Generation

Fuente: arXiv

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Bibliographic Details
Main Authors:	NVIDIA, :, Bala, Maciej, Cui, Yin, Ding, Yifan, Ge, Yunhao, Hao, Zekun, Hasselgren, Jon, Huffman, Jacob, Jin, Jingyi, Lewis, J. P., Li, Zhaoshuo, Lin, Chen-Hsuan, Lin, Yen-Chen, Lin, Tsung-Yi, Liu, Ming-Yu, Luo, Alice, Ma, Qianli, Munkberg, Jacob, Shi, Stella, Wei, Fangyin, Xiang, Donglai, Xu, Jiashu, Zeng, Xiaohui, Zhang, Qinsheng
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence Graphics
Online Access:	Acceder al recurso
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_version_	1866909384065417216
author	NVIDIA : Bala, Maciej Cui, Yin Ding, Yifan Ge, Yunhao Hao, Zekun Hasselgren, Jon Huffman, Jacob Jin, Jingyi Lewis, J. P. Li, Zhaoshuo Lin, Chen-Hsuan Lin, Yen-Chen Lin, Tsung-Yi Liu, Ming-Yu Luo, Alice Ma, Qianli Munkberg, Jacob Shi, Stella Wei, Fangyin Xiang, Donglai Xu, Jiashu Zeng, Xiaohui Zhang, Qinsheng
author_facet	NVIDIA : Bala, Maciej Cui, Yin Ding, Yifan Ge, Yunhao Hao, Zekun Hasselgren, Jon Huffman, Jacob Jin, Jingyi Lewis, J. P. Li, Zhaoshuo Lin, Chen-Hsuan Lin, Yen-Chen Lin, Tsung-Yi Liu, Ming-Yu Luo, Alice Ma, Qianli Munkberg, Jacob Shi, Stella Wei, Fangyin Xiang, Donglai Xu, Jiashu Zeng, Xiaohui Zhang, Qinsheng
contents	We introduce Edify 3D, an advanced solution designed for high-quality 3D asset generation. Our method first synthesizes RGB and surface normal images of the described object at multiple viewpoints using a diffusion model. The multi-view observations are then used to reconstruct the shape, texture, and PBR materials of the object. Our method can generate high-quality 3D assets with detailed geometry, clean shape topologies, high-resolution textures, and materials within 2 minutes of runtime.
format	Preprint
id	arxiv_https___arxiv_org_abs_2411_07135
institution	arXiv
publishDate	2024
record_format	arxiv
spellingShingle	Edify 3D: Scalable High-Quality 3D Asset Generation NVIDIA : Bala, Maciej Cui, Yin Ding, Yifan Ge, Yunhao Hao, Zekun Hasselgren, Jon Huffman, Jacob Jin, Jingyi Lewis, J. P. Li, Zhaoshuo Lin, Chen-Hsuan Lin, Yen-Chen Lin, Tsung-Yi Liu, Ming-Yu Luo, Alice Ma, Qianli Munkberg, Jacob Shi, Stella Wei, Fangyin Xiang, Donglai Xu, Jiashu Zeng, Xiaohui Zhang, Qinsheng Computer Vision and Pattern Recognition Artificial Intelligence Graphics We introduce Edify 3D, an advanced solution designed for high-quality 3D asset generation. Our method first synthesizes RGB and surface normal images of the described object at multiple viewpoints using a diffusion model. The multi-view observations are then used to reconstruct the shape, texture, and PBR materials of the object. Our method can generate high-quality 3D assets with detailed geometry, clean shape topologies, high-resolution textures, and materials within 2 minutes of runtime.
title	Edify 3D: Scalable High-Quality 3D Asset Generation
topic	Computer Vision and Pattern Recognition Artificial Intelligence Graphics
url	https://arxiv.org/abs/2411.07135