title: Chirpy3D: Continuous Part Latents for Creative 3D Bird Generation
summary: 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.
paper_authors._id: 677f9188fb22a3b146287a6c
paper_authors.name: Kam Woh Ng
paper_authors.status: admin_assigned
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paper_authors.fullname: kamwoh
paper_authors.type: user
paper_authors.user: kamwoh
paper_authors._id: 677f9188fb22a3b146287a6d
paper_authors.name: Jing Yang
paper_authors.status: admin_assigned
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paper_authors.fullname: George Young
paper_authors.type: user
paper_authors.user: jingyang
paper_authors._id: 677f9188fb22a3b146287a6e
paper_authors.name: Jia Wei Sii
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paper_authors.avatarUrl: /avatars/a69dd6959c0d2df7c08c321d2a4b4e98.svg
paper_authors.fullname: Jia Wei Sii
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paper_authors.user: siijiawei
paper_authors._id: 677f9188fb22a3b146287a6f
paper_authors.name: Jiankang Deng
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paper_authors.fullname: JiankangDeng
paper_authors.type: user
paper_authors.user: JiankangDeng
paper_authors._id: 677f9188fb22a3b146287a70
paper_authors.name: Chee Seng Chan
paper_authors.status: admin_assigned
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paper_authors._id: 65785c327ee8616c7c179e64
paper_authors.avatarUrl: /avatars/eb0a788aa05c5071e73885005f9f59c6.svg
paper_authors.fullname: Chee Seng Chan
paper_authors.type: user
paper_authors.user: cschan1313
paper_authors._id: 677f9188fb22a3b146287a71
paper_authors.name: Yi-Zhe Song
paper_authors._id: 677f9188fb22a3b146287a72
paper_authors.name: Tao Xiang
paper_authors._id: 677f9188fb22a3b146287a73
paper_authors.name: Xiatian Zhu
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-01-09T20:29:33.382Z
paper_authors._id: 647ef9e7aa8c04bbf9362a8a
paper_authors.avatarUrl: /avatars/dc23e15acf7ee7f3b9f1a68c2716a66d.svg
paper_authors.fullname: Xiatian Zhu
paper_authors.type: user
paper_authors.user: Xiatian-Zhu
paper_title: Chirpy3D: Continuous Part Latents for Creative 3D Bird Generation
paper_summary: 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.
paper_ai_keywords: 3D generation multi-view diffusion part latents continuous distributions interpolation sampling self-supervised feature consistency loss novelAP (Self-Supervised Multiview Attentional Projection technique) 3D objects species-specific details