Chirpy3D: Continuous Part Latents for Creative 3D Bird Generation
In this paper, we push the boundaries of fine-grained 3D generation into
truly creative territory. Current methods either lack intricate details or
simply mimic existing objects -- we enable both. By lifting 2D fine-grained
understanding into 3D through multi-view diffusion and modeling part latents as
continuous distributions, we unlock the ability to generate entirely new, yet
plausible parts through interpolation and sampling. A self-supervised feature
consistency loss further ensures stable generation of these unseen parts. The
result is the first system capable of creating novel 3D objects with
species-specific details that transcend existing examples. While we demonstrate
our approach on birds, the underlying framework extends beyond things that can
chirp! Code will be released at https://github.com/kamwoh/chirpy3d.
677f9188fb22a3b146287a6c
Kam Woh Ng
admin_assigned
2025-01-09T20:28:28.347Z
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kamwoh
user
kamwoh
677f9188fb22a3b146287a6d
Jing Yang
admin_assigned
2025-01-09T20:28:37.012Z
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George Young
user
jingyang
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Jia Wei Sii
admin_assigned
2025-01-09T20:28:43.193Z
668c0d460eeb9552cbd45989
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Jia Wei Sii
user
siijiawei
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Jiankang Deng
admin_assigned
2025-01-09T20:28:49.888Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/1657566065867-noauth.png
JiankangDeng
user
JiankangDeng
677f9188fb22a3b146287a70
Chee Seng Chan
admin_assigned
2025-01-09T20:28:55.545Z
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Chee Seng Chan
user
cschan1313
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Yi-Zhe Song
677f9188fb22a3b146287a72
Tao Xiang
677f9188fb22a3b146287a73
Xiatian Zhu
admin_assigned
2025-01-09T20:29:33.382Z
647ef9e7aa8c04bbf9362a8a
/avatars/dc23e15acf7ee7f3b9f1a68c2716a66d.svg
Xiatian Zhu
user
Xiatian-Zhu
Chirpy3D: Continuous Part Latents for Creative 3D Bird Generation
In this paper, we push the boundaries of fine-grained 3D generation into
truly creative territory. Current methods either lack intricate details or
simply mimic existing objects -- we enable both. By lifting 2D fine-grained
understanding into 3D through multi-view diffusion and modeling part latents as
continuous distributions, we unlock the ability to generate entirely new, yet
plausible parts through interpolation and sampling. A self-supervised feature
consistency loss further ensures stable generation of these unseen parts. The
result is the first system capable of creating novel 3D objects with
species-specific details that transcend existing examples. While we demonstrate
our approach on birds, the underlying framework extends beyond things that can
chirp! Code will be released at https://github.com/kamwoh/chirpy3d.
A system using multi-view diffusion and continuous part distributions generates novel, plausible 3D objects with fine-grained details that go beyond current examples.
multi-view diffusion continuous distributions interpolation sampling self-supervised feature consistency loss