title: 3D Gaussian Editing with A Single Image
summary: The modeling and manipulation of 3D scenes captured from the real world are
  pivotal in various applications, attracting growing research interest. While
  previous works on editing have achieved interesting results through
  manipulating 3D meshes, they often require accurately reconstructed meshes to
  perform editing, which limits their application in 3D content generation. To
  address this gap, we introduce a novel single-image-driven 3D scene editing
  approach based on 3D Gaussian Splatting, enabling intuitive manipulation via
  directly editing the content on a 2D image plane. Our method learns to optimize
  the 3D Gaussians to align with an edited version of the image rendered from a
  user-specified viewpoint of the original scene. To capture long-range object
  deformation, we introduce positional loss into the optimization process of 3D
  Gaussian Splatting and enable gradient propagation through reparameterization.
  To handle occluded 3D Gaussians when rendering from the specified viewpoint, we
  build an anchor-based structure and employ a coarse-to-fine optimization
  strategy capable of handling long-range deformation while maintaining
  structural stability. Furthermore, we design a novel masking strategy to
  adaptively identify non-rigid deformation regions for fine-scale modeling.
  Extensive experiments show the effectiveness of our method in handling
  geometric details, long-range, and non-rigid deformation, demonstrating
  superior editing flexibility and quality compared to previous approaches.
paper_authors._id: 66bd90fed5489e88f1a82462
paper_authors.name: Guan Luo
paper_authors._id: 66bd90fed5489e88f1a82463
paper_authors.name: Tian-Xing Xu
paper_authors._id: 66bd90fed5489e88f1a82464
paper_authors.name: Ying-Tian Liu
paper_authors._id: 66bd90fed5489e88f1a82465
paper_authors.name: Xiao-Xiong Fan
paper_authors._id: 66bd90fed5489e88f1a82466
paper_authors.name: Fang-Lue Zhang
paper_authors._id: 66bd90fed5489e88f1a82467
paper_authors.name: Song-Hai Zhang
paper_title: 3D Gaussian Editing with A Single Image
paper_summary: The modeling and manipulation of 3D scenes captured from the real world are
  pivotal in various applications, attracting growing research interest. While
  previous works on editing have achieved interesting results through
  manipulating 3D meshes, they often require accurately reconstructed meshes to
  perform editing, which limits their application in 3D content generation. To
  address this gap, we introduce a novel single-image-driven 3D scene editing
  approach based on 3D Gaussian Splatting, enabling intuitive manipulation via
  directly editing the content on a 2D image plane. Our method learns to optimize
  the 3D Gaussians to align with an edited version of the image rendered from a
  user-specified viewpoint of the original scene. To capture long-range object
  deformation, we introduce positional loss into the optimization process of 3D
  Gaussian Splatting and enable gradient propagation through reparameterization.
  To handle occluded 3D Gaussians when rendering from the specified viewpoint, we
  build an anchor-based structure and employ a coarse-to-fine optimization
  strategy capable of handling long-range deformation while maintaining
  structural stability. Furthermore, we design a novel masking strategy to
  adaptively identify non-rigid deformation regions for fine-scale modeling.
  Extensive experiments show the effectiveness of our method in handling
  geometric details, long-range, and non-rigid deformation, demonstrating
  superior editing flexibility and quality compared to previous approaches.
paper_ai_summary: A novel single-image-driven 3D scene editing approach using 3D Gaussian Splatting achieves intuitive manipulation via direct 2D image editing, capturing long-range and non-rigid deformations with superior quality.
paper_ai_keywords: 3D Gaussian Splatting positional loss reparameterization anchor-based structure coarse-to-fine optimization masking strategy non-rigid deformation