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pro vyhledávání: '"Carlos Rodriguez‐Pardo"'
Autor:
Carlos Rodriguez-Pardo, Elena Garces
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics. 29:2914-2925
We present SeamlessGAN, a method capable of automatically generating tileable texture maps from a single input exemplar. In contrast to most existing methods, focused solely on solving the synthesis problem, our work tackles both problems, synthesis
Autor:
Carlos Rodriguez-Pardo, Elena Garces
Publikováno v:
IEEE Transactions on Visualization and Computer Graphics. 29:1818-1830
We present a deep learning-based method for propagating spatially-varying visual material attributes (e.g. texture maps or image stylizations) to larger samples of the same or similar materials. For training, we leverage images of the material taken
We propose a method to estimate the mechanical parameters of fabrics using a casual capture setup with a depth camera. Our approach enables to create mechanically-correct digital representations of real-world textile materials, which is a fundamental
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f17b775f486dcab2c3bb4bd9a7b353b
Intrinsic imaging or intrinsic image decomposition has traditionally been described as the problem of decomposing an image into two layers: a reflectance, the albedo invariant color of the material; and a shading, produced by the interaction between
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14ec30a80bf88668ff4a0cfa780474db
http://arxiv.org/abs/2112.03842
http://arxiv.org/abs/2112.03842