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Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapes

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arxiv 2312.04043 v2 pith:GN33APHM submitted 2023-12-07 cs.CV cs.AI

classification cs.CVcs.AI
keywords modellingshapessketchesabstractapproachcorrespondencecross-modalpart-level
verification ladder T0 review T1 audit T2 compute T3 formal

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In this paper, we democratise 3D content creation, enabling precise generation of 3D shapes from abstract sketches while overcoming limitations tied to drawing skills. We introduce a novel part-level modelling and alignment framework that facilitates abstraction modelling and cross-modal correspondence. Leveraging the same part-level decoder, our approach seamlessly extends to sketch modelling by establishing correspondence between CLIPasso edgemaps and projected 3D part regions, eliminating the need for a dataset pairing human sketches and 3D shapes. Additionally, our method introduces a seamless in-position editing process as a byproduct of cross-modal part-aligned modelling. Operating in a low-dimensional implicit space, our approach significantly reduces computational demands and processing time.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. From Air to Wear: Personalized 3D Digital Fashion with AR/VR Immersive 3D Sketching

    cs.CV 2025-05 conditional novelty 5.0 of 10

    A VR-sketch-conditioned diffusion model, trained in three stages with curriculum learning and a new 969-pair dataset, generates plausible 3D garments from freehand 3D sketches.

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