Differentiable Vector Graphics Rasterization for Editing and Learning

Differentiable Vector Graphics Rasterization for Editing and Learning

We introduce a differentiable rasterizer that bridges the vector graphics and raster image domains, enabling powerful raster-based loss functions, optimization procedures, and machine learning techniques to edit and generate vector content. We observe that vector graphics rasterization is differenti...

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Bibliographic Details
Main Authors: Li, Tzu-Mao, Lukac, Mike, Gharbi, Michael, Ragan-Kelley, Jonathan
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:English
Published: ACM|SIGGRAPH Asia 2020 Technical Papers 2025
Online Access:https://hdl.handle.net/1721.1/158158

Internet

https://hdl.handle.net/1721.1/158158

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