CLIPtortionist: Zero-shot Text-driven Deformation for Manufactured 3D Shapes

• URL: http://arxiv.org/abs/2410.15199v1
• Date: Sat, 19 Oct 2024 20:11:11 GMT
• Title: CLIPtortionist: Zero-shot Text-driven Deformation for Manufactured 3D Shapes
• Authors: Xianghao Xu, Srinath Sridhar, Daniel Ritchie,
• Abstract summary: We propose a zero-shot text-driven 3D shape deformation system that deforms an input 3D mesh of a manufactured object to fit an input text description. We find that CLIP-based objective functions exhibit many spurious local optima; to circumvent them, we parameterize deformations using a novel deformation model called BoxDefGraph.
• Score: 15.985339563442189
• License:
• Abstract: We propose a zero-shot text-driven 3D shape deformation system that deforms an input 3D mesh of a manufactured object to fit an input text description. To do this, our system optimizes the parameters of a deformation model to maximize an objective function based on the widely used pre-trained vision language model CLIP. We find that CLIP-based objective functions exhibit many spurious local optima; to circumvent them, we parameterize deformations using a novel deformation model called BoxDefGraph which our system automatically computes from an input mesh, the BoxDefGraph is designed to capture the object aligned rectangular/circular geometry features of most manufactured objects. We then use the CMA-ES global optimization algorithm to maximize our objective, which we find to work better than popular gradient-based optimizers. We demonstrate that our approach produces appealing results and outperforms several baselines.

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