3D Gaussian Editing with A Single Image

• URL: http://arxiv.org/abs/2408.07540v1
• Date: Wed, 14 Aug 2024 13:17:42 GMT
• Title: 3D Gaussian Editing with A Single Image
• Authors: Guan Luo, Tian-Xing Xu, Ying-Tian Liu, Xiao-Xiong Fan, Fang-Lue Zhang, Song-Hai Zhang,
• Abstract summary: We introduce a novel single-image-driven 3D scene editing approach based on 3D Gaussian Splatting. Our method learns to optimize the 3D Gaussians to align with an edited version of the image rendered from a user-specified viewpoint. Experiments show the effectiveness of our method in handling geometric details, long-range, and non-rigid deformation.
• Score: 19.662680524312027
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

Related papers

• DragGaussian: Enabling Drag-style Manipulation on 3D Gaussian Representation [57.406031264184584]
  DragGaussian is a 3D object drag-editing framework based on 3D Gaussian Splatting. Our contributions include the introduction of a new task, the development of DragGaussian for interactive point-based 3D editing, and comprehensive validation of its effectiveness through qualitative and quantitative experiments.
  arXiv  Detail & Related papers  (2024-05-09T14:34:05Z)
• DGE: Direct Gaussian 3D Editing by Consistent Multi-view Editing [72.54566271694654]
  We consider the problem of editing 3D objects and scenes based on open-ended language instructions. A common approach to this problem is to use a 2D image generator or editor to guide the 3D editing process. This process is often inefficient due to the need for iterative updates of costly 3D representations.
  arXiv  Detail & Related papers  (2024-04-29T17:59:30Z)
• Sketch3D: Style-Consistent Guidance for Sketch-to-3D Generation [55.73399465968594]
  This paper proposes a novel generation paradigm Sketch3D to generate realistic 3D assets with shape aligned with the input sketch and color matching the textual description. Three strategies are designed to optimize 3D Gaussians, i.e., structural optimization via a distribution transfer mechanism, color optimization with a straightforward MSE loss and sketch similarity optimization with a CLIP-based geometric similarity loss.
  arXiv  Detail & Related papers  (2024-04-02T11:03:24Z)
• Diffusion Models are Geometry Critics: Single Image 3D Editing Using Pre-Trained Diffusion Priors [24.478875248825563]
  We propose a novel image editing technique that enables 3D manipulations on single images. Our method directly leverages powerful image diffusion models trained on a broad spectrum of text-image pairs. Our method can generate high-quality 3D-aware image edits with large viewpoint transformations and high appearance and shape consistency with the input image.
  arXiv  Detail & Related papers  (2024-03-18T06:18:59Z)
• GaussCtrl: Multi-View Consistent Text-Driven 3D Gaussian Splatting Editing [38.948892064761914]
  GaussCtrl is a text-driven method to edit a 3D scene reconstructed by the 3D Gaussian Splatting (3DGS) Our key contribution is multi-view consistent editing, which enables editing all images together instead of iteratively editing one image.
  arXiv  Detail & Related papers  (2024-03-13T17:35:28Z)
• GSEdit: Efficient Text-Guided Editing of 3D Objects via Gaussian Splatting [10.527349772993796]
  We present GSEdit, a pipeline for text-guided 3D object editing based on Gaussian Splatting models. Our method enables the editing of the style and appearance of 3D objects without altering their main details, all in a matter of minutes on consumer hardware.
  arXiv  Detail & Related papers  (2024-03-08T08:42:23Z)
• GaussianPro: 3D Gaussian Splatting with Progressive Propagation [49.918797726059545]
  3DGS relies heavily on the point cloud produced by Structure-from-Motion (SfM) techniques. We propose a novel method that applies a progressive propagation strategy to guide the densification of the 3D Gaussians. Our method significantly surpasses 3DGS on the dataset, exhibiting an improvement of 1.15dB in terms of PSNR.
  arXiv  Detail & Related papers  (2024-02-22T16:00:20Z)
• Learning Naturally Aggregated Appearance for Efficient 3D Editing [94.47518916521065]
  We propose to replace the color field with an explicit 2D appearance aggregation, also called canonical image. To avoid the distortion effect and facilitate convenient editing, we complement the canonical image with a projection field that maps 3D points onto 2D pixels for texture lookup. Our representation, dubbed AGAP, well supports various ways of 3D editing (e.g., stylization, interactive drawing, and content extraction) with no need of re-optimization.
  arXiv  Detail & Related papers  (2023-12-11T18:59:31Z)
• GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splatting [66.08674785436612]
  3D editing plays a crucial role in many areas such as gaming and virtual reality. Traditional 3D editing methods, which rely on representations like meshes and point clouds, often fall short in realistically depicting complex scenes. Our paper presents GaussianEditor, an innovative and efficient 3D editing algorithm based on Gaussian Splatting (GS), a novel 3D representation.
  arXiv  Detail & Related papers  (2023-11-24T14:46:59Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.