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Geometric Deformation on Objects: Unsupervised Image Manipulation via Conjugation

Fu, Changqing; Cohen, Laurent D. (2021), Geometric Deformation on Objects: Unsupervised Image Manipulation via Conjugation, Eighth International Conference on Scale Space and Variational Methods in Computer Vision (SSVM), 2021-05, on line, FRANCE

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SSVM21FINALarticle.pdf (815.8Kb)
Type
Communication / Conférence
Date
2021
Conference title
Eighth International Conference on Scale Space and Variational Methods in Computer Vision (SSVM)
Conference date
2021-05
Conference city
on line
Conference country
FRANCE
Metadata
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Author(s)
Fu, Changqing
Cohen, Laurent D.
Abstract (EN)
A novel two-stage approach is proposed for image manipulation and generation. User-interactive image deformation is performed through editing of contours. This is performed in the latent edge space with both color and gradient information. The output of editing is then fed into a multi-scale representation of the image to recover quality output. The model is flexible in terms of transferability and training efficiency.
Subjects / Keywords
Machine Learning; Image Generation; Generative Adversarial Network; Image deformation; Contour Editing

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