Papers Vector Graphics
“Vector Graphics” 태그가 달린 논문 88편 · 필터 해제
StrokeNUWA: Tokenizing Strokes for Vector Graphic Synthesis
To leverage LLMs for visual synthesis, traditional methods convert raster image information into discrete grid tokens through specialized visual modules, while disrupting the model's ability to capture the true semantic …
Vector GraphicsSymbol as Points: Panoptic Symbol Spotting via Point-based Representation
This work studies the problem of panoptic symbol spotting, which is to spot and parse both countable object instances (windows, doors, tables, etc.) and uncountable stuff (wall, railing, etc.) from computer-aided design …
Point Cloud SegmentationVector GraphicsVector Graphics Generation via Mutually Impulsed Dual-domain Diffusion
Intelligent generation of vector graphics has very promising applications in the fields of advertising and logo design artistic painting animation production etc. However current mainstream vector image generation me…
Image GenerationVector GraphicsSVGDreamer: Text Guided SVG Generation with Diffusion Model
Recently, text-guided scalable vector graphics (SVGs) synthesis has shown promise in domains such as iconography and sketch. However, existing text-to-SVG generation methods lack editability and struggle with visual qual…
DiversityVector GraphicsStarVector: Generating Scalable Vector Graphics Code from Images and Text
Scalable Vector Graphics (SVGs) are vital for modern image rendering due to their scalability and versatility. Previous SVG generation methods have focused on curve-based vectorization, lacking semantic understanding, of…
Code GenerationLanguage ModelingLanguage ModellingLarge Language Model+2VecFusion: Vector Font Generation with Diffusion
We present VecFusion, a new neural architecture that can generate vector fonts with varying topological structures and precise control point positions. Our approach is a cascaded diffusion model which consists of a raste…
Font GenerationVector GraphicsBeyond Pixels: Exploring Human-Readable SVG Generation for Simple Images with Vision Language Models
In the field of computer graphics, the use of vector graphics, particularly Scalable Vector Graphics (SVG), represents a notable development from traditional pixel-based imagery. SVGs, with their XML-based format, are di…
Vector GraphicsPosterior Distillation Sampling
We introduce Posterior Distillation Sampling (PDS), a novel optimization method for parametric image editing based on diffusion models. Existing optimization-based methods, which leverage the powerful 2D prior of diffusi…
AttributeVector GraphicsSAMVG: A Multi-stage Image Vectorization Model with the Segment-Anything Model
Vector graphics are widely used in graphical designs and have received more and more attention. However, unlike raster images which can be easily obtained, acquiring high-quality vector graphics, typically through automa…
Image SegmentationmodelSegmentationSemantic Segmentation+1AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ
Generating bitmap graphics from text has gained considerable attention, yet for scientific figures, vector graphics are often preferred. Given that vector graphics are typically encoded using low-level graphics primitive…
Language ModelingLanguage ModellingLarge Language ModelMemorization+1Text-Guided Vector Graphics Customization
Vector graphics are widely used in digital art and valued by designers for their scalability and layer-wise topological properties. However, the creation and editing of vector graphics necessitate creativity and design e…
Vector GraphicsA Theory of Topological Derivatives for Inverse Rendering of Geometry
We introduce a theoretical framework for differentiable surface evolution that allows discrete topology changes through the use of topological derivatives for variational optimization of image functionals. While prior me…
3D ReconstructionImage ReconstructionInverse RenderingMulti-View 3D Reconstruction+1Image Vectorization: a Review
Nowadays, there are many diffusion and autoregressive models that show impressive results for generating images from text and other input domains. However, these methods are not intended for ultra-high-resolution image s…
Image GenerationVector GraphicsLeveraging Large Language Models for Scalable Vector Graphics-Driven Image Understanding
Large language models (LLMs) have made significant advancements in natural language understanding. However, through that enormous semantic representation that the LLM has learnt, is it somehow possible for it to understa…
Few-Shot Learningimage-classificationImage ClassificationIn-Context Learning+5Automating Style Analysis and Visualization With Explainable AI -- Case Studies on Brand Recognition
Incorporating style-related objectives into shape design has been centrally important to maximize product appeal. However, stylistic features such as aesthetics and semantic attributes are hard to codify even for experts…
Graph Neural NetworkVector GraphicsIconShop: Text-Guided Vector Icon Synthesis with Autoregressive Transformers
Scalable Vector Graphics (SVG) is a popular vector image format that offers good support for interactivity and animation. Despite its appealing characteristics, creating custom SVG content can be challenging for users du…
DiversityImage GenerationText to Image GenerationText-to-Image Generation+1SuperpixelGraph: Semi-automatic generation of building footprint through semantic-sensitive superpixel and neural graph networks
Most urban applications necessitate building footprints in the form of concise vector graphics with sharp boundaries rather than pixel-wise raster images. This need contrasts with the majority of existing methods, which …
SegmentationSemantic SegmentationSuperpixelsVector GraphicsDeepVecFont-v2: Exploiting Transformers to Synthesize Vector Fonts with Higher Quality
Vector font synthesis is a challenging and ongoing problem in the fields of Computer Vision and Computer Graphics. The recently-proposed DeepVecFont achieved state-of-the-art performance by exploiting information of both…
DecoderVector GraphicsNeural Style Transfer for Vector Graphics
Neural style transfer draws researchers' attention, but the interest focuses on bitmap images. Various models have been developed for bitmap image generation both online and offline with arbitrary and pre-trained styles.…
Image GenerationStyle TransferVector GraphicsVectorFloorSeg: Two-Stream Graph Attention Network for Vectorized Roughcast Floorplan Segmentation
Vector graphics (VG) are ubiquitous in industrial designs. In this paper, we address semantic segmentation of a typical VG, i.e., roughcast floorplans with bare wall structures, whose output can be directly used for …
Graph AttentionSegmentationSemantic SegmentationVector Graphics