Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapes
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866909218870657024 |
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| author | Bandyopadhyay, Hmrishav Koley, Subhadeep Das, Ayan Bhunia, Ayan Kumar Sain, Aneeshan Chowdhury, Pinaki Nath Xiang, Tao Song, Yi-Zhe |
| author_facet | Bandyopadhyay, Hmrishav Koley, Subhadeep Das, Ayan Bhunia, Ayan Kumar Sain, Aneeshan Chowdhury, Pinaki Nath Xiang, Tao Song, Yi-Zhe |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_04043 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapes Bandyopadhyay, Hmrishav Koley, Subhadeep Das, Ayan Bhunia, Ayan Kumar Sain, Aneeshan Chowdhury, Pinaki Nath Xiang, Tao Song, Yi-Zhe Computer Vision and Pattern Recognition Artificial Intelligence 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. |
| title | Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapes |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2312.04043 |