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Sketch-Based Modeling of Parametric Shapes
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Sketch-Based Modeling of Parametric Shapes

Bastien Wailly, Adrien Bousseau
Misc - 2019
Download the publication : deep_sketch.pdf [1.7Mo]  
We demonstrate a sketch-based modeling system running on a multi-touch pen tablet. Our system takes inspiration from the work of Nishida et al., who proposed to use deep convolutional networks to interpret sketches of parametric shapes. While Nishida et al. applied this approach to the creation of procedural buildings, we focus on the creation of simple shapes (cuboids, cylinders, cones, spheres, pyramids) that users can assemble to create more complex objects. In this poster we describe the main components of our system -- the deep convolutional networks used for sketch interpretation, the training data, the user interface, and the overall software architecture that combines these components.

This work was presented at Expressive 2019 - Posters, Demos, and Artworks

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This work was supported by the ERC starting grant D3 (ERC-2016- STG 714221) and research and software donations from Adobe.

BibTex references

@Misc{WB19,
  author       = "Wailly, Bastien and Bousseau, Adrien",
  title        = "Sketch-Based Modeling of Parametric Shapes",
  year         = "2019",
  url          = "http://www-sop.inria.fr/reves/Basilic/2019/WB19"
}

Other publications in the database

» Adrien Bousseau