iShapEditing: Intelligent Shape Editing with Diffusion Models

IF 2.7 4区 计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING Computer Graphics Forum Pub Date : 2024-11-08 DOI:10.1111/cgf.15253
Jing Li, Juyong Zhang, Falai Chen
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Abstract

Recent advancements in generative models have enabled image editing very effective with impressive results. By extending this progress to 3D geometry models, we introduce iShapEditing, a novel framework for 3D shape editing which is applicable to both generated and real shapes. Users manipulate shapes by dragging handle points to corresponding targets, offering an intuitive and intelligent editing interface. Leveraging the Triplane Diffusion model and robust intermediate feature correspondence, our framework utilizes classifier guidance to adjust noise representations during sampling process, ensuring alignment with user expectations while preserving plausibility. For real shapes, we employ shape predictions at each time step alongside a DDPM-based inversion algorithm to derive their latent codes, facilitating seamless editing. iShapEditing provides effective and intelligent control over shapes without the need for additional model training or fine-tuning. Experimental examples demonstrate the effectiveness and superiority of our method in terms of editing accuracy and plausibility.

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iShapEditing:利用扩散模型进行智能形状编辑
生成模型的最新进展使图像编辑变得非常有效,效果令人印象深刻。通过将这一进展扩展到三维几何模型,我们引入了 iShapEditing,这是一种新颖的三维形状编辑框架,既适用于生成的形状,也适用于真实的形状。用户通过拖动手柄点到相应的目标来操作形状,提供了一个直观、智能的编辑界面。利用三平面扩散模型和稳健的中间特征对应关系,我们的框架在采样过程中利用分类器引导来调整噪声表示,确保与用户期望保持一致,同时保留可信度。对于真实形状,我们在每个时间步采用形状预测和基于 DDPM 的反演算法来推导其潜在代码,从而促进无缝编辑。iShapEditing 可对形状进行有效的智能控制,而无需额外的模型训练或微调。实验实例证明了我们的方法在编辑准确性和可信度方面的有效性和优越性。
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来源期刊
Computer Graphics Forum
Computer Graphics Forum 工程技术-计算机:软件工程
CiteScore
5.80
自引率
12.00%
发文量
175
审稿时长
3-6 weeks
期刊介绍: Computer Graphics Forum is the official journal of Eurographics, published in cooperation with Wiley-Blackwell, and is a unique, international source of information for computer graphics professionals interested in graphics developments worldwide. It is now one of the leading journals for researchers, developers and users of computer graphics in both commercial and academic environments. The journal reports on the latest developments in the field throughout the world and covers all aspects of the theory, practice and application of computer graphics.
期刊最新文献
DiffPop: Plausibility-Guided Object Placement Diffusion for Image Composition Front Matter LGSur-Net: A Local Gaussian Surface Representation Network for Upsampling Highly Sparse Point Cloud 𝒢-Style: Stylized Gaussian Splatting iShapEditing: Intelligent Shape Editing with Diffusion Models
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