Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Rodriguez‐Pardo, Carlos"'
We introduce TexTile, a novel differentiable metric to quantify the degree upon which a texture image can be concatenated with itself without introducing repeating artifacts (i.e., the tileability). Existing methods for tileable texture synthesis foc
Externí odkaz:
http://arxiv.org/abs/2403.12961
Publikováno v:
Computers & Graphics, Volume 114, 2023, Pages 239-246, ISSN 0097-8493
Neural material representations are becoming a popular way to represent materials for rendering. They are more expressive than analytic models and occupy less memory than tabulated BTFs. However, existing neural materials are immutable, meaning that
Externí odkaz:
http://arxiv.org/abs/2307.01199
Publikováno v:
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, BC, Canada, 2023 pp. 5764-5774
We propose a learning-based method to recover normals, specularity, and roughness from a single diffuse image of a material, using microgeometry appearance as our primary cue. Previous methods that work on single images tend to produce over-smooth ou
Externí odkaz:
http://arxiv.org/abs/2305.16312
Publikováno v:
Computer Graphics Forum, 42: 149-160, 2023
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:
http://arxiv.org/abs/2304.06704
Autor:
Rodriguez-Pardo, Carlos, Garces, Elena
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
Externí odkaz:
http://arxiv.org/abs/2201.05120
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:
http://arxiv.org/abs/2112.03842
Autor:
Rodriguez-Pardo, Carlos, Garces, Elena
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
Externí odkaz:
http://arxiv.org/abs/2112.02520
Autor:
Rodríguez-Pardo, Carlos, Bilen, Hakan
The use of computational methods to evaluate aesthetics in photography has gained interest in recent years due to the popularization of convolutional neural networks and the availability of new annotated datasets. Most studies in this area have focus
Externí odkaz:
http://arxiv.org/abs/1907.03802
Autor:
Rodriguez‐Pardo, Carlos1,2 (AUTHOR), Fabre, Javier1,2 (AUTHOR), Garces, Elena1,2 (AUTHOR), Lopez‐Moreno, Jorge1,2 (AUTHOR)
Publikováno v:
Computer Graphics Forum. Jul2023, Vol. 42 Issue 4, p1-14. 14p. 7 Color Photographs, 2 Charts, 2 Graphs.
Publikováno v:
In Computers & Graphics October 2019 83:33-41