title: AvatarVerse: High-quality & Stable 3D Avatar Creation from Text and Pose
summary: Creating expressive, diverse and high-quality 3D avatars from highly
  customized text descriptions and pose guidance is a challenging task, due to
  the intricacy of modeling and texturing in 3D that ensure details and various
  styles (realistic, fictional, etc). We present AvatarVerse, a stable pipeline
  for generating expressive high-quality 3D avatars from nothing but text
  descriptions and pose guidance. In specific, we introduce a 2D diffusion model
  conditioned on DensePose signal to establish 3D pose control of avatars through
  2D images, which enhances view consistency from partially observed scenarios.
  It addresses the infamous Janus Problem and significantly stablizes the
  generation process. Moreover, we propose a progressive high-resolution 3D
  synthesis strategy, which obtains substantial improvement over the quality of
  the created 3D avatars. To this end, the proposed AvatarVerse pipeline achieves
  zero-shot 3D modeling of 3D avatars that are not only more expressive, but also
  in higher quality and fidelity than previous works. Rigorous qualitative
  evaluations and user studies showcase AvatarVerse's superiority in synthesizing
  high-fidelity 3D avatars, leading to a new standard in high-quality and stable
  3D avatar creation. Our project page is: https://avatarverse3d.github.io
paper_authors._id: 64d1d0429cff738203befffb
paper_authors.name: Huichao Zhang
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-08-09T00:42:55.538Z
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paper_authors.avatarUrl: /avatars/90bf6156b649b78db13f08d0770951ad.svg
paper_authors.fullname: zhanghuichao
paper_authors.type: user
paper_authors.user: liqingzju
paper_authors._id: 64d1d0429cff738203befffc
paper_authors.name: Bowen Chen
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-08-08T14:33:57.343Z
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paper_authors.avatarUrl: /avatars/b3ae6888a41aab8c2a7ef9f7320565c4.svg
paper_authors.fullname: Bowen Chen 
paper_authors.type: user
paper_authors.user: chenbowen
paper_authors._id: 64d1d0429cff738203befffd
paper_authors.name: Hao Yang
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-08-10T01:13:53.951Z
paper_authors._id: 6322d55796d6c8518eaff8c5
paper_authors.avatarUrl: /avatars/7309e77145674d01dbd842b0dcda171f.svg
paper_authors.fullname: Hao Yang
paper_authors.type: user
paper_authors.user: hayaalex
paper_authors._id: 64d1d0429cff738203befffe
paper_authors.name: Liao Qu
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-08-08T13:44:33.486Z
paper_authors._id: 64b796079ebb7e6c7ddcdabf
paper_authors.avatarUrl: /avatars/51af43cab078705b8745b4f942f542e5.svg
paper_authors.fullname: Liao Qu
paper_authors.type: user
paper_authors.user: leo1117
paper_authors._id: 64d1d0429cff738203beffff
paper_authors.name: Xu Wang
paper_authors._id: 64d1d0429cff738203bf0000
paper_authors.name: Li Chen
paper_authors._id: 64d1d0429cff738203bf0001
paper_authors.name: Chao Long
paper_authors._id: 64d1d0429cff738203bf0002
paper_authors.name: Feida Zhu
paper_authors._id: 64d1d0429cff738203bf0003
paper_authors.name: Kang Du
paper_authors._id: 64d1d0429cff738203bf0004
paper_authors.name: Min Zheng
paper_title: AvatarVerse: High-quality & Stable 3D Avatar Creation from Text and Pose
paper_summary: Creating expressive, diverse and high-quality 3D avatars from highly
  customized text descriptions and pose guidance is a challenging task, due to
  the intricacy of modeling and texturing in 3D that ensure details and various
  styles (realistic, fictional, etc). We present AvatarVerse, a stable pipeline
  for generating expressive high-quality 3D avatars from nothing but text
  descriptions and pose guidance. In specific, we introduce a 2D diffusion model
  conditioned on DensePose signal to establish 3D pose control of avatars through
  2D images, which enhances view consistency from partially observed scenarios.
  It addresses the infamous Janus Problem and significantly stablizes the
  generation process. Moreover, we propose a progressive high-resolution 3D
  synthesis strategy, which obtains substantial improvement over the quality of
  the created 3D avatars. To this end, the proposed AvatarVerse pipeline achieves
  zero-shot 3D modeling of 3D avatars that are not only more expressive, but also
  in higher quality and fidelity than previous works. Rigorous qualitative
  evaluations and user studies showcase AvatarVerse's superiority in synthesizing
  high-fidelity 3D avatars, leading to a new standard in high-quality and stable
  3D avatar creation. Our project page is: https://avatarverse3d.github.io
paper_ai_summary: AvatarVerse generates high-fidelity 3D avatars from text descriptions and pose guidance using a 2D diffusion model and progressive high-resolution synthesis.
paper_ai_keywords: 2D diffusion model DensePose signal 3D pose control view consistency Janus Problem progressive high-resolution 3D synthesis zero-shot 3D modeling high-fidelity 3D avatars