Learning-based Artificial Intelligence Artwork: Methodology Taxonomy and Quality Evaluation
With the development of the theory and technology of computer science, machine or
computer painting is increasingly being explored in the creation of art. Machine-made works …
computer painting is increasingly being explored in the creation of art. Machine-made works …
Stroke-based neural painting and stylization with dynamically predicted painting region
Stroke-based rendering aims to recreate an image with a set of strokes. Most existing
methods render complex images using an uniform-block-dividing strategy, which leads to …
methods render complex images using an uniform-block-dividing strategy, which leads to …
Artificial intelligence for geometry-based feature extraction, analysis and synthesis in artistic images: a survey
Artificial Intelligence significantly enhances the visual art industry by analyzing, identifying
and generating digitized artistic images. This review highlights the substantial benefits of …
and generating digitized artistic images. This review highlights the substantial benefits of …
Painterly Style Transfer With Learned Brush Strokes
Real-world paintings are made, by artists, using brush strokes as the rendering primitive to
depict semantic content. The bulk of the Neural Style Transfer (NST) is known transferring …
depict semantic content. The bulk of the Neural Style Transfer (NST) is known transferring …
ProcessPainter: Learning to draw from sequence data
The painting process of artists is inherently stepwise and varies significantly among different
painters and styles. Generating detailed, step-by-step painting processes is essential for art …
painters and styles. Generating detailed, step-by-step painting processes is essential for art …
Towards Artist-Like Painting Agents with Multi-Granularity Semantic Alignment
Mainstream painting agents based on stroke-based rendering (SBR) attempt to translate
visual appearance into a sequence of vectorized painting-style strokes. Lacking a direct …
visual appearance into a sequence of vectorized painting-style strokes. Lacking a direct …
ProcessPainter: Learn Painting Process from Sequence Data
The painting process of artists is inherently stepwise and varies significantly among different
painters and styles. Generating detailed, step-by-step painting processes is essential for art …
painters and styles. Generating detailed, step-by-step painting processes is essential for art …
Image representation and reconstruction by compositing Gaussian ellipses
CC Cheng - IET Image Processing, 2024 - Wiley Online Library
In this paper, a method of stroke‐based rendering is proposed for image representation and
reconstruction. The proposed method involves compositing a set of ellipses that greatly vary …
reconstruction. The proposed method involves compositing a set of ellipses that greatly vary …
Optimal Image Transport on Sparse Dictionaries
J Huang, H Wang, A Weiermann… - arxiv preprint arxiv …, 2023 - arxiv.org
In this paper, we derive a novel optimal image transport algorithm over sparse dictionaries
by taking advantage of Sparse Representation (SR) and Optimal Transport (OT). Concisely …
by taking advantage of Sparse Representation (SR) and Optimal Transport (OT). Concisely …
AttentionPainter: An Efficient and Adaptive Stroke Predictor for Scene Painting
Stroke-based Rendering (SBR) aims to decompose an input image into a sequence of
parameterized strokes, which can be rendered into a painting that resembles the input …
parameterized strokes, which can be rendered into a painting that resembles the input …