Cited By
View all- Wang QMao ZGao JZhang Y(2024)Document-level Relation Extraction with Progressive Self-distillationACM Transactions on Information Systems10.1145/365616842:6(1-34)Online publication date: 25-Jun-2024
Patternshop: Editing Point Patterns by Image Manipulation
Authors: 
Xingchang Huang, Tobias Ritschel, Hans-Peter Seidel, Pooran Memari, Gurprit SinghAuthors Info & Claims
Xingchang Huang, Tobias Ritschel, Hans-Peter Seidel, Pooran Memari, Gurprit SinghAuthors Info & ClaimsArticle No.: 53, Pages 1 - 14
Abstract
Point patterns are characterized by their density and correlation. While spatial variation of density is well-understood, analysis and synthesis of spatially-varying correlation is an open challenge. No tools are available to intuitively edit such point patterns, primarily due to the lack of a compact representation for spatially varying correlation. We propose a low-dimensional perceptual embedding for point correlations. This embedding can map point patterns to common three-channel raster images, enabling manipulation with off-the-shelf image editing software. To synthesize back point patterns, we propose a novel edge-aware objective that carefully handles sharp variations in density and correlation. The resulting framework allows intuitive and backward-compatible manipulation of point patterns, such as recoloring, relighting to even texture synthesis that have not been available to 2D point pattern design before. Effectiveness of our approach is tested in several user experiments. Code is available at https://github.com/xchhuang/patternshop.
Supplementary Material
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- Patternshop: Editing Point Patterns by Image Manipulation
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Published: 26 July 2023
Published in TOG Volume 42, Issue 4
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View all- Wang QMao ZGao JZhang Y(2024)Document-level Relation Extraction with Progressive Self-distillationACM Transactions on Information Systems10.1145/365616842:6(1-34)Online publication date: 25-Jun-2024
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