doi:10.1111/cgf.14446engDelanoy, J.Lagunas, M.Condor, J.Gutierrez, D.Masia, B.A generative framework for image-based editing of material appearance using perceptual attributesART-2022-131513Single-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.2022http://zaguan.unizar.es/record/12690610.1111/cgf.14446http://zaguan.unizar.es/record/126906oai:zaguan.unizar.es:126906info:eu-repo/grantAgreement/EC/H2020/682080/EU/Intuitive editing of visual appearance from real-world datasets/CHAMELEONThis project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 682080-CHAMELEONinfo:eu-repo/grantAgreement/EC/H2020/765121/EU/DyViTo: Dynamics in Vision and Touch - the look and feel of stuff/DyViToThis project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 765121-DyViToinfo:eu-repo/grantAgreement/EC/H2020/956585/EU/Predictive Rendering In Manufacture and Engineering/PRIMEThis project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 956585-PRIMEComputer Graphics Forum 41, 1 (2022), 453-464All rights reservedhttp://www.europeana.eu/rights/rr-f/info:eu-repo/semantics/openAccess