126906 20240319081014.0 doi 10.1111/cgf.14446 sideral 131513 ART-2022-131513 eng Delanoy, J. A generative framework for image-based editing of material appearance using perceptual attributes 2022 Access copy available to the general public Unrestricted Single-image appearance editing is a challenging task, traditionally requiring the estimation of additional scene properties such as geometry or illumination. Moreover, the exact interaction of light, shape and material reflectance that elicits a given perceptual impression is still not well understood. We present an image-based editing method that allows to modify the material appearance of an object by increasing or decreasing high-level perceptual attributes, using a single image as input. Our framework relies on a two-step generative network, where the first step drives the change in appearance and the second produces an image with high-frequency details. For training, we augment an existing material appearance dataset with perceptual judgements of high-level attributes, collected through crowd-sourced experiments, and build upon training strategies that circumvent the cumbersome need for original-edited image pairs. We demonstrate the editing capabilities of our framework on a variety of inputs, both synthetic and real, using two common perceptual attributes (Glossy and Metallic), and validate the perception of appearance in our edited images through a user study. info:eu-repo/grantAgreement/EC/H2020/682080/EU/Intuitive editing of visual appearance from real-world datasets/CHAMELEON This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 682080-CHAMELEON info:eu-repo/grantAgreement/EC/H2020/765121/EU/DyViTo: Dynamics in Vision and Touch - the look and feel of stuff/DyViTo This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 765121-DyViTo info:eu-repo/grantAgreement/EC/H2020/956585/EU/Predictive Rendering In Manufacture and Engineering/PRIME This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 956585-PRIME info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 2.5 2022 COMPUTER SCIENCE, SOFTWARE ENGINEERING 52 / 108 = 0.481 2022 Q2 T2 0.95 2022 Computer Networks and Communications 2022 Q1 Computer Graphics and Computer-Aided Design 2022 Q1 5.3 2022 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Lagunas, M. Condor, J. Gutierrez, D. Universidad de Zaragoza (orcid)0000-0002-7503-7022 Masia, B. Universidad de Zaragoza (orcid)0000-0003-0060-7278 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 41, 1 (2022), 453-464 Comput. graph. forum Computer Graphics Forum 0167-7055 2240857 http://zaguan.unizar.es/record/126906/files/texto_completo.pdf Postprint 2174449 http://zaguan.unizar.es/record/126906/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:126906 articulos driver 2024-03-18-15:28:44 ARTICLE