Neural Contours: Learning to Draw Lines From 3D Shapes
Difan Liu, Mohamed Nabail, Aaron Hertzmann, Evangelos Kalogerakis
2020Year
11Top-tier citations
Abstract
Adobe Research Figure 1 : Given a 3D model (left), our network creates a line drawing that conveys its structure more accurately compared to using other methods individually, such as Occluding Contours [1], Apparent Ridges [22] , and pix2pix variants [37] . Please see appendix for results on many more models.
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Install the CLIlune papers fulltext 9b18a453-37de-48fa-a66b-3cf0748c73adCited by top-tier papers11
- Learning to generate line drawings that convey geometry and semanticsCaroline Chan, Frédo Durand, Phillip IsolaCVPR 2022 · 86 citations
- Neural Strokes: Stylized Line Drawing of 3D ShapesDifan Liu, Matthew Fisher, Aaron Hertzmann, Evangelos KalogerakisICCV 2021 · 29 citations
- SketchEmbedNet: Learning Novel Concepts by Imitating DrawingsAlexander Wang, Mengye Ren, Richard S. ZemelICML 2021 · 24 citations
- Tracing versus freehand for evaluating computer-generated drawingsZeyu Wang, Sherry Qiu, Nicole Feng, Holly E. Rushmeier et al.SIGGRAPH 2021 · 20 citations
- VecFusion: Vector Font Generation with DiffusionVikas Thamizharasan, Difan Liu, Shantanu Agarwal, Matthew Fisher et al.CVPR 2024 · 18 citations
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