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awesome-architectural-graphics

Collection of recent advanced computer graphics research that involved potential architectural application
https://github.com/jockyuiz/awesome-architectural-graphics

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2. Architectural Geometry
- 3) Deployable system
- 4) 3D shape-to-sketch
- 5) Sketch(vector)-to-sketch(vector)
  - Animated Construction of Line Drawings
- 6) Art-to-sketch
  - StrokeAggregator: Consolidating Raw Sketches into Artist-Intended Curve Drawings
  - StrokeStrip: Joint Parameterization and Fitting of Stroke Clusters
  - Topology-Driven Vectorization of Clean Line Drawings
  - Fidelity vs. Simplicity: a Global Approach to Line Drawing Vectorization - sop.inria.fr/reves/Basilic/2016/FLB16/) | Optimization |
  - A Delaunay triangulation based approach for cleaning rough sketches
  - Semantic Segmentation for Line Drawing Vectorization Using Neural Networks
  - Integer-Grid Sketch Simplification and Vectorization - sam.inria.fr/d3/grid-vectorization/) [[Code]](https://gitlab.inria.fr/D3/grid-vectorization/) | Optimization |
  - Deep Vectorization of Technical Drawings - Vectorization-of-Technical-Drawings) | Learning |
  - General Virtual Sketching Framework for Vector Line Art
  - Keypoint-Driven Line Drawing Vectorization via PolyVector Flow - driven-polyvector-flow/) | Learning + Optimization |
  - End-to-end Line Drawing Vectorization
  - Vectorizing Line Drawings of Arbitrary Thickness via Boundary-based Topology Reconstruction
  - Learning to Simplify: Fully Convolutional Networks for Rough Sketch Cleanup
  - Mastering Sketching: Adversarial Augmentation for Structured Prediction
  - Real-Time Data-Driven Interactive Rough Sketch Inking
  - Generating Manga from Illustrations via Mimicking Manga Workflow
  - MangaGAN: Unpaired Photo-to-Manga Translation Based on The Methodology of Manga Drawing
  - Vectorization of Raster Manga by Deep Reinforcement Learning
  - Deep extraction of manga structural lines
  - Inertia-based Fast Vectorization of Line Drawings
  - Vectorization of Line Drawings via Polyvector Fields
  - Deep Line Drawing Vectorization via Line Subdivision and Topology Reconstruction
  - Perceptual-aware Sketch Simplification Based on Integrated VGG Layers
  - Deep extraction of manga structural lines
  - Manga Filling Style Conversion with Screentone Variational Autoencoder
3. Inverse CAD Modeling
- 6) Art-to-sketch
  - Synthesizing Programs for Images using Reinforced Adversarial Learning
  - Unsupervised Doodling and Painting with Improved SPIRAL - to-paint.github.io/) |
  - Towards Layer-wise Image Vectorization - xu/LIVE) [[project]](https://ma-xu.github.io/LIVE/) |
  - Paint Transformer: Feed Forward Neural Painting with Stroke Prediction
  - Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes - parameterized-style-transfer) |
  - Im2Vec: Synthesizing Vector Graphics without Vector Supervision
  - Stylized Neural Painting - neural-painting) [[project]](https://jiupinjia.github.io/neuralpainter/) |
  - Strokenet: A neural painting environment
  - Neural Painters: A learned differentiable constraint for generating brushstroke paintings - painters-pytorch) |
  - Learning to Sketch with Deep Q Networks and Demonstrated Strokes
  - Unsupervised Image to Sequence Translation with Canvas-Drawer Networks
  - Perception-Driven Semi-Structured Boundary Vectorization
  - PolyFit: Perception-aligned Vectorization of Raster Clip-art via Intermediate Polygonal Fitting
  - ClipGen: A Deep Generative Model for Clipart Vectorization and Synthesis
  - Depixelizing pixel art
  - TCB-Spline-Based Image Vectorization

Categories

2. Architectural Geometry 36 3. Inverse CAD Modeling 16

Sub Categories

6) Art-to-sketch 41 3) Deployable system 6 4) 3D shape-to-sketch 4 5) Sketch(vector)-to-sketch(vector) 1