TexTile: A Differentiable Metric for Texture Tileability

dc.affiliation.dptoInformática y Estadística
dc.affiliation.grupoinvMultimodal Simulation Lab (MSLab)
dc.contributor.authorRodriguez-Pardo, Carlos
dc.contributor.authorCasas, Dan
dc.contributor.authorGarces, Elena
dc.contributor.authorLopez-Moreno, Jorge
dc.contributor.funderMCIN/AEI (Ministerio de Ciencia e Innovación / Agencia Estatal de Investigación, España), NextGenerationEU
dc.date.accessioned2026-01-29T08:07:17Z
dc.date.issued2024-06-17
dc.description.abstractWe 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 focus on general texture quality, but lack explicit analysis of the intrinsic repeatability properties of a texture. In contrast, our TexTile metric effectively evaluates the tileable properties of a texture, opening the door to more informed synthesis and analysis of tileable textures. Under the hood, TexTile is formulated as a binary classifier carefully built from a large dataset of textures of different styles, semantics, regularities, and human annotations.
dc.identifier.citationRodriguez-Pardo, C., Casas, D., Garces, E., & Lopez-Moreno, J. (2024). TexTile: A Differentiable Metric for Texture Tileability. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 4439-4449).
dc.identifier.doi10.48550/arXiv.2403.12961
dc.identifier.publicationtitleProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
dc.identifier.urihttps://hdl.handle.net/10115/154617
dc.language.isoen_US
dc.publisherIEEE / Computer Vision Foundation (CVF)
dc.relation.eventdate2024-06-17
dc.relation.eventplaceSeattle, WA, USA
dc.relation.eventtitleIEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2024)
dc.relation.projectCodeCPP2021-008842
dc.relation.projectCodeIJC2020-044192-I
dc.relation.projectNameTaiLOR
dc.relation.projectNameJuan de la Cierva - Incorporacion
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectTexture Tileability
dc.subjectDifferentiable Metric
dc.subjectTexture Synthesis
dc.subjectNeural Networks
dc.subjectComputer Vision
dc.subjectImage Quality Assessment (IQA)
dc.titleTexTile: A Differentiable Metric for Texture Tileability
dc.typeArticle

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