3DSwapping: Texture Swapping For 3D Object From Single Reference Image
- URL: http://arxiv.org/abs/2503.18853v1
- Date: Mon, 24 Mar 2025 16:31:52 GMT
- Title: 3DSwapping: Texture Swapping For 3D Object From Single Reference Image
- Authors: Xiao Cao, Beibei Lin, Bo Wang, Zhiyong Huang, Robby T. Tan,
- Abstract summary: 3D texture swapping allows for the customization of 3D object textures.<n>No dedicated method exists, but adapted 2D editing and text-driven 3D editing approaches can serve this purpose.<n>We introduce 3DSwapping, a 3D texture swapping method that integrates progressive generation, view-consistency gradient guidance, and prompt-tuned gradient guidance.
- Score: 21.454340647455236
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 3D texture swapping allows for the customization of 3D object textures, enabling efficient and versatile visual transformations in 3D editing. While no dedicated method exists, adapted 2D editing and text-driven 3D editing approaches can serve this purpose. However, 2D editing requires frame-by-frame manipulation, causing inconsistencies across views, while text-driven 3D editing struggles to preserve texture characteristics from reference images. To tackle these challenges, we introduce 3DSwapping, a 3D texture swapping method that integrates: 1) progressive generation, 2) view-consistency gradient guidance, and 3) prompt-tuned gradient guidance. To ensure view consistency, our progressive generation process starts by editing a single reference image and gradually propagates the edits to adjacent views. Our view-consistency gradient guidance further reinforces consistency by conditioning the generation model on feature differences between consistent and inconsistent outputs. To preserve texture characteristics, we introduce prompt-tuning-based gradient guidance, which learns a token that precisely captures the difference between the reference image and the 3D object. This token then guides the editing process, ensuring more consistent texture preservation across views. Overall, 3DSwapping integrates these novel strategies to achieve higher-fidelity texture transfer while preserving structural coherence across multiple viewpoints. Extensive qualitative and quantitative evaluations confirm that our three novel components enable convincing and effective 2D texture swapping for 3D objects. Code will be available upon acceptance.
Related papers
- Advancing 3D Gaussian Splatting Editing with Complementary and Consensus Information [4.956066467858058]
We present a novel framework for enhancing the visual fidelity and consistency of text-guided 3D Gaussian Splatting (3DGS) editing.<n>Our method demonstrates superior performance in rendering quality and view consistency compared to state-of-the-art approaches.
arXiv Detail & Related papers (2025-03-14T17:15:26Z) - DragScene: Interactive 3D Scene Editing with Single-view Drag Instructions [9.31257776760014]
3D editing has shown remarkable capability in editing scenes based on various instructions.
Existing methods struggle with achieving intuitive, localized editing.
We introduce DragScene, a framework that integrates drag-style editing with diverse 3D representations.
arXiv Detail & Related papers (2024-12-18T07:02:01Z) - Chat-Edit-3D: Interactive 3D Scene Editing via Text Prompts [76.73043724587679]
We propose a dialogue-based 3D scene editing approach, termed CE3D.
Hash-Atlas represents 3D scene views, which transfers the editing of 3D scenes onto 2D atlas images.
Results demonstrate that CE3D effectively integrates multiple visual models to achieve diverse editing visual effects.
arXiv Detail & Related papers (2024-07-09T13:24:42Z) - SyncNoise: Geometrically Consistent Noise Prediction for Text-based 3D Scene Editing [58.22339174221563]
We propose SyncNoise, a novel geometry-guided multi-view consistent noise editing approach for high-fidelity 3D scene editing.
SyncNoise synchronously edits multiple views with 2D diffusion models while enforcing multi-view noise predictions to be geometrically consistent.
Our method achieves high-quality 3D editing results respecting the textual instructions, especially in scenes with complex textures.
arXiv Detail & Related papers (2024-06-25T09:17:35Z) - Reference-Based 3D-Aware Image Editing with Triplanes [15.222454412573455]
Generative Adversarial Networks (GANs) have emerged as powerful tools for high-quality image generation and real image editing by manipulating their latent spaces.
Recent advancements in GANs include 3D-aware models such as EG3D, which feature efficient triplane-based architectures capable of reconstructing 3D geometry from single images.
This study addresses this gap by exploring and demonstrating the effectiveness of the triplane space for advanced reference-based edits.
arXiv Detail & Related papers (2024-04-04T17:53:33Z) - View-Consistent 3D Editing with Gaussian Splatting [50.6460814430094]
View-consistent Editing (VcEdit) is a novel framework that seamlessly incorporates 3DGS into image editing processes.<n>By incorporating consistency modules into an iterative pattern, VcEdit proficiently resolves the issue of multi-view inconsistency.
arXiv Detail & Related papers (2024-03-18T15:22:09Z) - DragTex: Generative Point-Based Texture Editing on 3D Mesh [11.163205302136625]
We propose a generative point-based 3D mesh texture editing method called DragTex.
This method utilizes a diffusion model to blend locally inconsistent textures in the region near the deformed silhouette between different views.
We train LoRA using multi-view images instead of training each view individually, which significantly shortens the training time.
arXiv Detail & Related papers (2024-03-04T17:05:01Z) - Image Sculpting: Precise Object Editing with 3D Geometry Control [33.9777412846583]
Image Sculpting is a new framework for editing 2D images by incorporating tools from 3D geometry and graphics.
It supports precise, quantifiable, and physically-plausible editing options such as pose editing, rotation, translation, 3D composition, carving, and serial addition.
arXiv Detail & Related papers (2024-01-02T18:59:35Z) - Learning Naturally Aggregated Appearance for Efficient 3D Editing [90.57414218888536]
We learn the color field as an explicit 2D appearance aggregation, also called canonical image.
We complement the canonical image with a projection field that maps 3D points onto 2D pixels for texture query.
Our approach demonstrates remarkable efficiency by being at least 20 times faster per edit compared to existing NeRF-based editing methods.
arXiv Detail & Related papers (2023-12-11T18:59:31Z) - TeMO: Towards Text-Driven 3D Stylization for Multi-Object Meshes [67.5351491691866]
We present a novel framework, dubbed TeMO, to parse multi-object 3D scenes and edit their styles.
Our method can synthesize high-quality stylized content and outperform the existing methods over a wide range of multi-object 3D meshes.
arXiv Detail & Related papers (2023-12-07T12:10:05Z) - Self-Supervised Geometry-Aware Encoder for Style-Based 3D GAN Inversion [115.82306502822412]
StyleGAN has achieved great progress in 2D face reconstruction and semantic editing via image inversion and latent editing.
A corresponding generic 3D GAN inversion framework is still missing, limiting the applications of 3D face reconstruction and semantic editing.
We study the challenging problem of 3D GAN inversion where a latent code is predicted given a single face image to faithfully recover its 3D shapes and detailed textures.
arXiv Detail & Related papers (2022-12-14T18:49:50Z)
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.