title: RoomDreamer: Text-Driven 3D Indoor Scene Synthesis with Coherent
    Geometry and Texture
summary: The techniques for 3D indoor scene capturing are widely used, but the meshes
  produced leave much to be desired. In this paper, we propose "RoomDreamer",
  which leverages powerful natural language to synthesize a new room with a
  different style. Unlike existing image synthesis methods, our work addresses
  the challenge of synthesizing both geometry and texture aligned to the input
  scene structure and prompt simultaneously. The key insight is that a scene
  should be treated as a whole, taking into account both scene texture and
  geometry. The proposed framework consists of two significant components:
  Geometry Guided Diffusion and Mesh Optimization. Geometry Guided Diffusion for
  3D Scene guarantees the consistency of the scene style by applying the 2D prior
  to the entire scene simultaneously. Mesh Optimization improves the geometry and
  texture jointly and eliminates the artifacts in the scanned scene. To validate
  the proposed method, real indoor scenes scanned with smartphones are used for
  extensive experiments, through which the effectiveness of our method is
  demonstrated.
paper_authors._id: 646abab435c7a57f936bee50
paper_authors.name: Liangchen Song
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-05-23T09:46:37.283Z
paper_authors._id: 63d9ea2aaefaa7352587151c
paper_authors.avatarUrl: /avatars/2f02ee1b2a0018c74ef1d47883782bd5.svg
paper_authors.fullname: LSong
paper_authors.type: user
paper_authors.user: lsongx
paper_authors._id: 646abab435c7a57f936bee51
paper_authors.name: Liangliang Cao
paper_authors._id: 646abab435c7a57f936bee52
paper_authors.name: Hongyu Xu
paper_authors._id: 646abab435c7a57f936bee53
paper_authors.name: Kai Kang
paper_authors._id: 646abab435c7a57f936bee54
paper_authors.name: Feng Tang
paper_authors._id: 646abab435c7a57f936bee55
paper_authors.name: Junsong Yuan
paper_authors._id: 646abab435c7a57f936bee56
paper_authors.name: Yang Zhao
paper_title: RoomDreamer: Text-Driven 3D Indoor Scene Synthesis with Coherent
    Geometry and Texture
paper_summary: The techniques for 3D indoor scene capturing are widely used, but the meshes
  produced leave much to be desired. In this paper, we propose "RoomDreamer",
  which leverages powerful natural language to synthesize a new room with a
  different style. Unlike existing image synthesis methods, our work addresses
  the challenge of synthesizing both geometry and texture aligned to the input
  scene structure and prompt simultaneously. The key insight is that a scene
  should be treated as a whole, taking into account both scene texture and
  geometry. The proposed framework consists of two significant components:
  Geometry Guided Diffusion and Mesh Optimization. Geometry Guided Diffusion for
  3D Scene guarantees the consistency of the scene style by applying the 2D prior
  to the entire scene simultaneously. Mesh Optimization improves the geometry and
  texture jointly and eliminates the artifacts in the scanned scene. To validate
  the proposed method, real indoor scenes scanned with smartphones are used for
  extensive experiments, through which the effectiveness of our method is
  demonstrated.
paper_ai_summary: RoomDreamer synthesizes 3D indoor scenes with desired styles by aligning geometry and texture using Geometry Guided Diffusion and Mesh Optimization.
paper_ai_keywords: Geometry Guided Diffusion Mesh Optimization 3D indoor scene synthesis scene structure prompt scene texture scene geometry artifacts smartphone scanning