iShapEditing: Intelligent Shape Editing with Diffusion Models

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dc.contributor.authorLi, Jingen_US
dc.contributor.authorZhang, Juyongen_US
dc.contributor.authorChen, Falaien_US
dc.contributor.editorChen, Renjieen_US
dc.contributor.editorRitschel, Tobiasen_US
dc.contributor.editorWhiting, Emilyen_US
dc.date.accessioned2024-10-13T18:09:38Z
dc.date.available2024-10-13T18:09:38Z
dc.date.issued2024
dc.description.abstractRecent 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.en_US
dc.description.number7
dc.description.sectionheaders3D Modeling and Editing
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume43
dc.identifier.doi10.1111/cgf.15253
dc.identifier.issn1467-8659
dc.identifier.pages15 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.15253
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf15253
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies → Shape editing; Diffusion model; Classifier guidance
dc.subjectComputing methodologies → Shape editing
dc.subjectDiffusion model
dc.subjectClassifier guidance
dc.titleiShapEditing: Intelligent Shape Editing with Diffusion Modelsen_US
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