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Related papers: Order-Independent Texture Synthesis

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Training defect detection algorithms for visual surface inspection systems requires a large and representative set of training data. Often there is not enough real data available which additionally cannot cover the variety of possible…

Computational Engineering, Finance, and Science · Computer Science 2024-03-21 Natascha Jeziorski , Claudia Redenbach

Single image super-resolution is the task of inferring a high-resolution image from a single low-resolution input. Traditionally, the performance of algorithms for this task is measured using pixel-wise reconstruction measures such as peak…

Computer Vision and Pattern Recognition · Computer Science 2018-01-16 Mehdi S. M. Sajjadi , Bernhard Schölkopf , Michael Hirsch

We present a generative method for texture filtering, which exhibits surprisingly good performance and generalizability. Our core idea is to empower texture filtering by taking full advantage of the strong learned image prior of pre-trained…

Computer Vision and Pattern Recognition · Computer Science 2026-04-22 Rongjia Zheng , Shangwei Huang , Lei Zhu , Wei-Shi Zheng , Qing Zhang

Natural images can be viewed as patchworks of different textures, where the local image statistics is roughly stationary within a small neighborhood but otherwise varies from region to region. In order to model this variability, we first…

Computer Vision and Pattern Recognition · Computer Science 2015-05-29 Niklas Ludtke , Debapriya Das , Lucas Theis , Matthias Bethge

Texture classification became one of the problems which has been paid much attention on by image processing scientists since late 80s. Consequently, since now many different methods have been proposed to solve this problem. In most of these…

Computer Vision and Pattern Recognition · Computer Science 2011-09-07 Shervan Fekri Ershad

In this work, we propose a system that covers the complete workflow for achieving controlled authoring and editing of textures that present distinctive local characteristics. These include various effects that change the surface appearance…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Andrei-Timotei Ardelean , Tim Weyrich

This article introduces the Stochastic Texture Difference method for analyzing data at prescribed spatial and value scales. This method relies on constrained random walks around each pixel, describing how nearby image values typically…

Computer Vision and Pattern Recognition · Computer Science 2015-10-06 Nicolas Brodu , Hussein Yahia

Restricting path tracing to a small number of paths per pixel for performance reasons rarely achieves a satisfactory image quality for scenes of interest. However, path space filtering may dramatically improve the visual quality by sharing…

Graphics · Computer Science 2021-02-04 Nikolaus Binder , Sascha Fricke , Alexander Keller

Synthesizing photo-realistic images and videos is at the heart of computer graphics and has been the focus of decades of research. Traditionally, synthetic images of a scene are generated using rendering algorithms such as rasterization or…

Texture is one of the most important properties of visual surface that helps in discriminating one object from another or an object from background. The self-organizing map (SOM) is an excellent tool in exploratory phase of data mining. It…

Computer Vision and Pattern Recognition · Computer Science 2014-08-20 Marghny H. Mohamed , Mohammed M. Abdelsamea

This paper presents an efficient method for texture retrieval using multiscale feature extraction and embedding based on the local extrema keypoints. The idea is to first represent each texture image by its local maximum and local minimum…

Computer Vision and Pattern Recognition · Computer Science 2018-08-06 Minh-Tan Pham

Recently, deep generative adversarial networks for image generation have advanced rapidly; yet, only a small amount of research has focused on generative models for irregular structures, particularly meshes. Nonetheless, mesh generation and…

Graphics · Computer Science 2020-08-20 Amir Hertz , Rana Hanocka , Raja Giryes , Daniel Cohen-Or

This paper investigates a novel task of generating texture images from perceptual descriptions. Previous work on texture generation focused on either synthesis from examples or generation from procedural models. Generating textures from…

Computer Vision and Pattern Recognition · Computer Science 2017-03-30 Yanhai Gan , Huifang Chi , Ying Gao , Jun Liu , Guoqiang Zhong , Junyu Dong

Recently, enthusiastic studies have devoted to texture synthesis using deep neural networks, because these networks excel at handling complex patterns in images. In these models, second-order statistics, such as Gram matrix, are used to…

Computer Vision and Pattern Recognition · Computer Science 2018-07-31 Zi-Ming Wang , Gui-Song Xia , Yi-Peng Zhang

Assessing the synthesizability of inorganic materials is a grand challenge for accelerating their discovery using computations. Synthesis of a material is a complex process that depends not only on its thermodynamic stability with respect…

While recent 3D generative models can produce high-quality texture images, they often fail to capture human preferences or meet task-specific requirements. Moreover, a core challenge in the 3D texture generation domain is that most existing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 AmirHossein Zamani , Tianhao Xie , Amir G. Aghdam , Tiberiu Popa , Eugene Belilovsky

There has been significant progress in generating an animatable 3D human avatar from a single image. However, recovering texture for the 3D human avatar from a single image has been relatively less addressed. Because the generated 3D human…

Computer Vision and Pattern Recognition · Computer Science 2023-05-02 Sihun Cha , Kwanggyoon Seo , Amirsaman Ashtari , Junyong Noh

Synthetic data used for scene text detection and recognition tasks have proven effective. However, there are still two problems: First, the color schemes used for text coloring in the existing methods are relatively fixed color key-value…

Computer Vision and Pattern Recognition · Computer Science 2022-11-02 Shao Wei Wang , Guan Jie Huang , Xiang Yu Luo

We propose a novel method of efficient upsampling of a single natural image. Current methods for image upsampling tend to produce high-resolution images with either blurry salient edges, or loss of fine textural detail, or spurious noise…

Computer Vision and Pattern Recognition · Computer Science 2015-03-03 Chinmay Hegde , Oncel Tuzel , Fatih Porikli

The following article introduces a new parametric synthesis algorithm for sound textures inspired by existing methods used for visual textures. Using a 2D Convolutional Neural Network (CNN), a sound signal is modified until the temporal…

Sound · Computer Science 2019-05-10 Hugo Caracalla , Axel Roebel
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