Vector Graphics

12 papers with code • 0 benchmarks • 1 datasets

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Datasets


Most implemented papers

FloorNet: A Unified Framework for Floorplan Reconstruction from 3D Scans

art-programmer/FloorNet ECCV 2018

The ultimate goal of this indoor mapping research is to automatically reconstruct a floorplan simply by walking through a house with a smartphone in a pocket.

A Learned Representation for Scalable Vector Graphics

tensorflow/magenta ICCV 2019

Dramatic advances in generative models have resulted in near photographic quality for artificially rendered faces, animals and other objects in the natural world.

DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation

alexandre01/deepsvg NeurIPS 2020

Scalable Vector Graphics (SVG) are ubiquitous in modern 2D interfaces due to their ability to scale to different resolutions.

Recognizing Vector Graphics without Rasterization

microsoft/YOLaT-VectorGraphicsRecognition NeurIPS 2021

In this paper, we consider a different data format for images: vector graphics.

Infomap Bioregions: Interactive mapping of biogeographical regions from species distributions

mapequation/bioregions 30 Nov 2016

As examples of applications, researchers can reconstruct ancestral ranges in historical biogeography or identify indicator species for targeted conservation.

Raster-To-Vector: Revisiting Floorplan Transformation

art-programmer/FloorplanTransformation ICCV 2017

A neural architecture first transforms a rasterized image to a set of junctions that represent low-level geometric and semantic information (e. g., wall corners or door end-points).

UV-Net: Learning from Boundary Representations

AutodeskAILab/UV-Net CVPR 2021

We introduce UV-Net, a novel neural network architecture and representation designed to operate directly on Boundary representation (B-rep) data from 3D CAD models.

Differentiable Vector Graphics Rasterization for Editing and Learning

BachiLi/diffvg ACM Transactions on Graphics 2020

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.

Im2Vec: Synthesizing Vector Graphics without Vector Supervision

preddy5/Im2Vec CVPR 2021

The current alternative is to use specialized models that require explicit supervision on the vector graphics representation at training time.

SVG-Net: An SVG-based Trajectory Prediction Model

vita-epfl/SVGNet 7 Oct 2021

Finally, we illustrate how, by using SVG, one can benefit from datasets and advancements in other research fronts that also utilize the same input format.