title: Vista3D: Unravel the 3D Darkside of a Single Image
summary: We embark on the age-old quest: unveiling the hidden dimensions of objects
  from mere glimpses of their visible parts. To address this, we present Vista3D,
  a framework that realizes swift and consistent 3D generation within a mere 5
  minutes. At the heart of Vista3D lies a two-phase approach: the coarse phase
  and the fine phase. In the coarse phase, we rapidly generate initial geometry
  with Gaussian Splatting from a single image. In the fine phase, we extract a
  Signed Distance Function (SDF) directly from learned Gaussian Splatting,
  optimizing it with a differentiable isosurface representation. Furthermore, it
  elevates the quality of generation by using a disentangled representation with
  two independent implicit functions to capture both visible and obscured aspects
  of objects. Additionally, it harmonizes gradients from 2D diffusion prior with
  3D-aware diffusion priors by angular diffusion prior composition. Through
  extensive evaluation, we demonstrate that Vista3D effectively sustains a
  balance between the consistency and diversity of the generated 3D objects.
  Demos and code will be available at https://github.com/florinshen/Vista3D.
paper_authors._id: 66ebcde43716e7e4fa9606fd
paper_authors.name: Qiuhong Shen
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-09-19T09:07:35.385Z
paper_authors._id: 643a6e89a856622f9788bf67
paper_authors.avatarUrl: /avatars/419c0379f072295b27d4bfe2f8fb946d.svg
paper_authors.fullname: qiuhong shen
paper_authors.type: user
paper_authors.user: florinshum
paper_authors._id: 66ebcde43716e7e4fa9606fe
paper_authors.name: Xingyi Yang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-09-19T09:07:42.089Z
paper_authors._id: 634cfebc350bcee9bed20a4d
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/634cfebc350bcee9bed20a4d/fN47nN5rhw-HJaFLBZWQy.png
paper_authors.fullname: Xingyi Yang
paper_authors.type: user
paper_authors.user: adamdad
paper_authors._id: 66ebcde43716e7e4fa9606ff
paper_authors.name: Michael Bi Mi
paper_authors._id: 66ebcde43716e7e4fa960700
paper_authors.name: Xinchao Wang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-09-19T09:08:11.384Z
paper_authors._id: 63fc03a50aab060792ffef39
paper_authors.avatarUrl: /avatars/9d5b1bb2a41928e08176b703935133ab.svg
paper_authors.fullname: Wangxinchao
paper_authors.type: user
paper_authors.user: wxcTest
paper_title: Vista3D: Unravel the 3D Darkside of a Single Image
paper_summary: We embark on the age-old quest: unveiling the hidden dimensions of objects
  from mere glimpses of their visible parts. To address this, we present Vista3D,
  a framework that realizes swift and consistent 3D generation within a mere 5
  minutes. At the heart of Vista3D lies a two-phase approach: the coarse phase
  and the fine phase. In the coarse phase, we rapidly generate initial geometry
  with Gaussian Splatting from a single image. In the fine phase, we extract a
  Signed Distance Function (SDF) directly from learned Gaussian Splatting,
  optimizing it with a differentiable isosurface representation. Furthermore, it
  elevates the quality of generation by using a disentangled representation with
  two independent implicit functions to capture both visible and obscured aspects
  of objects. Additionally, it harmonizes gradients from 2D diffusion prior with
  3D-aware diffusion priors by angular diffusion prior composition. Through
  extensive evaluation, we demonstrate that Vista3D effectively sustains a
  balance between the consistency and diversity of the generated 3D objects.
  Demos and code will be available at https://github.com/florinshen/Vista3D.
paper_ai_summary: Vista3D framework generates 3D models from 2D images using Gaussian Splatting and disentangled implicit functions, combining 2D and 3D diffusion priors for improved quality and consistency.
paper_ai_keywords: Gaussian Splatting Signed Distance Function differentiable isosurface representation implicit functions disentangled representation 2D diffusion prior 3D-aware diffusion priors angular diffusion prior composition