One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View
  Generation and 3D Diffusion
Recent advancements in open-world 3D object generation have been remarkable,
with image-to-3D methods offering superior fine-grained control over their
text-to-3D counterparts. However, most existing models fall short in
simultaneously providing rapid generation speeds and high fidelity to input
images - two features essential for practical applications. In this paper, we
present One-2-3-45++, an innovative method that transforms a single image into
a detailed 3D textured mesh in approximately one minute. Our approach aims to
fully harness the extensive knowledge embedded in 2D diffusion models and
priors from valuable yet limited 3D data. This is achieved by initially
finetuning a 2D diffusion model for consistent multi-view image generation,
followed by elevating these images to 3D with the aid of multi-view conditioned
3D native diffusion models. Extensive experimental evaluations demonstrate that
our method can produce high-quality, diverse 3D assets that closely mirror the
original input image. Our project webpage:
https://sudo-ai-3d.github.io/One2345plus_page.
65544370f7f0fcad58b387e9
Minghua Liu
admin_assigned
2023-11-15T09:34:52.896Z
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Minghua Liu
user
minghua
65544370f7f0fcad58b387ea
Ruoxi Shi
admin_assigned
2023-11-15T09:39:30.020Z
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Ruoxi Shi
user
eliphatfs
65544370f7f0fcad58b387eb
Linghao Chen
admin_assigned
2023-11-15T09:39:37.904Z
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Linghao Chen
user
fsky097
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Zhuoyang Zhang
admin_assigned
2023-11-15T09:39:44.847Z
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Zhuoyang Zhang
user
zhuoyang20
65544370f7f0fcad58b387ed
Chao Xu
claimed_verified
2023-11-15T08:18:59.481Z
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Chao Xu
user
chaoxu
65544370f7f0fcad58b387ee
Xinyue Wei
admin_assigned
2023-11-15T09:39:51.658Z
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Xinyue Wei
user
sarahwei0210
65544370f7f0fcad58b387ef
Hansheng Chen
admin_assigned
2023-11-15T09:40:10.762Z
638067fcb334960c987fbeda
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Hansheng Chen
user
Lakonik
65544370f7f0fcad58b387f0
Chong Zeng
admin_assigned
2023-11-15T09:40:18.182Z
60747cbf3ea03830676542b5
https://cdn-avatars.huggingface.co/v1/production/uploads/60747cbf3ea03830676542b5/wGr1Jzz520JM9nZ-UcLyb.png
Chong Zeng
user
NCJ
65544370f7f0fcad58b387f1
Jiayuan Gu
admin_assigned
2023-11-15T09:40:26.405Z
638aa283cebef0d13aa2ec2e
/avatars/3b67e6a6073033864a817230e97c27ca.svg
Jiayuan Gu
user
jigu
65544370f7f0fcad58b387f2
Hao Su
One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View
  Generation and 3D Diffusion
Recent advancements in open-world 3D object generation have been remarkable,
with image-to-3D methods offering superior fine-grained control over their
text-to-3D counterparts. However, most existing models fall short in
simultaneously providing rapid generation speeds and high fidelity to input
images - two features essential for practical applications. In this paper, we
present One-2-3-45++, an innovative method that transforms a single image into
a detailed 3D textured mesh in approximately one minute. Our approach aims to
fully harness the extensive knowledge embedded in 2D diffusion models and
priors from valuable yet limited 3D data. This is achieved by initially
finetuning a 2D diffusion model for consistent multi-view image generation,
followed by elevating these images to 3D with the aid of multi-view conditioned
3D native diffusion models. Extensive experimental evaluations demonstrate that
our method can produce high-quality, diverse 3D assets that closely mirror the
original input image. Our project webpage:
https://sudo-ai-3d.github.io/One2345plus_page.
One-2-3-45++ generates detailed 3D meshes from a single image using fine-tuned 2D diffusion models and multi-view conditioned 3D diffusion models, balancing speed and quality.
image-to-3D methods text-to-3D counterparts rapid generation speeds high fidelity 2D diffusion models multi-view image generation multi-view conditioned 3D native diffusion models