--- res: bibo_abstract: - Material appearance hinges on material reflectance properties but also surface geometry and illumination. The unlimited number of potential combinations between these factors makes understanding and predicting material appearance a very challenging task. In this work, we collect a large-scale dataset of perceptual ratings of appearance attributes with more than 215,680 responses for 42,120 distinct combinations of material, shape, and illumination. The goal of this dataset is twofold. First, we analyze for the first time the effects of illumination and geometry in material perception across such a large collection of varied appearances. We connect our findings to those of the literature, discussing how previous knowledge generalizes across very diverse materials, shapes, and illuminations. Second, we use the collected dataset to train a deep learning architecture for predicting perceptual attributes that correlate with human judgments. We demonstrate the consistent and robust behavior of our predictor in various challenging scenarios, which, for the first time, enables estimating perceived material attributes from general 2D images. Since our predictor relies on the final appearance in an image, it can compare appearance properties across different geometries and illumination conditions. Finally, we demonstrate several applications that use our predictor, including appearance reproduction using 3D printing, BRDF editing by integrating our predictor in a differentiable renderer, illumination design, or material recommendations for scene design.@eng bibo_authorlist: - foaf_Person: foaf_givenName: Ana foaf_name: Serrano, Ana foaf_surname: Serrano - foaf_Person: foaf_givenName: Bin foaf_name: Chen, Bin foaf_surname: Chen - foaf_Person: foaf_givenName: Chao foaf_name: Wang, Chao foaf_surname: Wang - foaf_Person: foaf_givenName: Michael foaf_name: Piovarci, Michael foaf_surname: Piovarci foaf_workInfoHomepage: http://www.librecat.org/personId=62E473F4-5C99-11EA-A40E-AF823DDC885E orcid: 0000-0002-5062-4474 - foaf_Person: foaf_givenName: Hans Peter foaf_name: Seidel, Hans Peter foaf_surname: Seidel - foaf_Person: foaf_givenName: Piotr foaf_name: Didyk, Piotr foaf_surname: Didyk - foaf_Person: foaf_givenName: Karol foaf_name: Myszkowski, Karol foaf_surname: Myszkowski bibo_doi: 10.1145/3450626.3459813 bibo_issue: '4' bibo_volume: 40 dct_date: 2021^xs_gYear dct_identifier: - UT:000674930900090 dct_isPartOf: - http://id.crossref.org/issn/07300301 - http://id.crossref.org/issn/15577368 dct_language: eng dct_publisher: Association for Computing Machinery@ dct_title: 'The effect of shape and illumination on material perception: Model and applications@' ...