Patternshop: Editing Point Patterns by Image Manipulation -- Supplemental Webpage
Xingchang Huang, Max-Planck-Institut für Informatik, Germany
Tobias Ritschel, University College London, United Kingdom
Hans-Peter Seidel, Max-Planck-Institut für Informatik, Germany
Pooran Memari, CNRS, LIX, École Polytechnique, IP Paris, INRIA, France
Gurprit Singh, Max-Planck-Institut für Informatik, Germany
We provide additional results on different applications. Please click on the links to see the results.
Summary:
- We use the network trained on tree cover density dataset to reconstruct density and correlation map from the following point distributions generated by our synthesis method.
- It shows the possibility to train our network on other datasets for different purposes, e.g., point pattern expansion.
- We show that we can reconstruct spatially-varying correlation and achieve automatic non-stationary point pattern expansion, while preserving the correlation.
- We show identity edits at the end to check the quality of network output and re-synthesis.
The PDF link of the pointsets are provided on top of the pointset images. Please zoom-in or right-click for downloading if needed.
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1: Input points 
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Network output 
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Editing (content-aware fill in Adobe Photoshop 2022) 
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Our edit-aware synthesis [PDF] 
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2: Input points 
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Network output 
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Editing (content-aware fill in Adobe Photoshop 2022) 
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Our edit-aware synthesis [PDF] 
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3: Input points 
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Network output 
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Editing (content-aware fill in Adobe Photoshop 2022) 
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Our edit-aware synthesis [PDF] 
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4: Input points 
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Network output 
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Editing (content-aware fill in Adobe Photoshop 2022) 
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Our edit-aware synthesis [PDF] 
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5: Input points 
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Network output 
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Editing (content-aware fill in Adobe Photoshop 2022) 
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Our edit-aware synthesis [PDF] 
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6: Input points 
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Network output 
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Editing (content-aware fill in Adobe Photoshop 2022) 
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Our edit-aware synthesis [PDF] 
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7: Input points 
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Network output 
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Editing (content-aware fill in Adobe Photoshop 2022) 
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Our edit-aware synthesis [PDF] 
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8: Input points
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Network output
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Editing (identity) 
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Our edit-aware synthesis [PDF] 
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9: Input points
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Network output
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Editing (identity) 
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Our edit-aware synthesis [PDF] 
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10: Input points
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Network output
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Editing (identity) 
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Our edit-aware synthesis [PDF] 
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11: Input points
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Network output
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Editing (identity) 
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Our edit-aware synthesis [PDF] 
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12: Input points
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Network output
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Editing (identity) 
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Our edit-aware synthesis [PDF] 
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13: Input points 
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Network output 
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Editing (identity) 
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Our edit-aware synthesis [PDF] 
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14: Input points
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Network output
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Editing (identity) 
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Our edit-aware synthesis [PDF] 
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15: Input points
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Network output
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Editing (identity) 
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Our edit-aware synthesis [PDF] 
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