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Automatic extraction and synthesis of regular repeatable patterns

Published: 01 October 2019 Publication History

Highlights

Automatic method capable of synthesizing regular repeating patterns in images.
Latent spaces of convolutional networks are used to find minimum tileable patterns.
Image regularization improve consistency in the estimation of the pattern.
Deep perceptual metrics are effective evaluating the quality of the texture tiling.

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Abstract

Textures made of regular repeating patterns are ubiquitous in the real world, most notably in man-made environments. They are defined by the presence of a repeating element, which can show a significant amount of random variations, non-rigid deformations or color noise. We propose an end-to-end pipeline capable of finding the size of the minimal repeating pattern in single images, as well as obtaining the single repetition that, when tiled, produces the most similar synthesis to the complete image. We do this by combining state-of-the-art algorithms in image transformations, repeating pattern detection, image stitching and deep perceptual losses. Additionally, we show how our pipeline can find the minimal color pattern in woven fabrics, which can be useful for both surface-based render methods and computer vision tasks in the textile domain.

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  1. Automatic extraction and synthesis of regular repeatable patterns
        Index terms have been assigned to the content through auto-classification.

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        Published In

        cover image Computers and Graphics
        Computers and Graphics  Volume 83, Issue C
        Oct 2019
        122 pages

        Publisher

        Pergamon Press, Inc.

        United States

        Publication History

        Published: 01 October 2019

        Author Tags

        1. Computers and graphics
        2. Computer vision
        3. Image representations
        4. Interest point and salient region detection
        5. Shape inference
        6. Machine learning

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        • (2024)Content-aware Tile Generation using Exterior Boundary InpaintingACM Transactions on Graphics10.1145/368798143:6(1-12)Online publication date: 19-Dec-2024
        • (2024)Generative Escher MeshesACM SIGGRAPH 2024 Conference Papers10.1145/3641519.3657452(1-11)Online publication date: 13-Jul-2024
        • (2024)TexSliders: Diffusion-Based Texture Editing in CLIP SpaceACM SIGGRAPH 2024 Conference Papers10.1145/3641519.3657444(1-11)Online publication date: 13-Jul-2024
        • (2024)Woven Fabric Capture with a Reflection-Transmission Photo PairACM SIGGRAPH 2024 Conference Papers10.1145/3641519.3657410(1-10)Online publication date: 13-Jul-2024
        • (2024)The use of CNNs in VR/AR/MR/XR: a systematic literature reviewVirtual Reality10.1007/s10055-024-01044-628:3Online publication date: 30-Aug-2024
        • (2023)SeamlessGAN: Self-Supervised Synthesis of Tileable Texture MapsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.314361529:6(2914-2925)Online publication date: 1-Jun-2023
        • (2022)U-Attention to Textures: Hierarchical Hourglass Vision Transformer for Universal Texture SynthesisProceedings of the 19th ACM SIGGRAPH European Conference on Visual Media Production10.1145/3565516.3565525(1-10)Online publication date: 1-Dec-2022
        • (2022)Woven Fabric Capture from a Single PhotoSIGGRAPH Asia 2022 Conference Papers10.1145/3550469.3555380(1-8)Online publication date: 29-Nov-2022

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