Texel-Att: Representing and Classifying Element-Based Textures by Attributes

Marco Godi (University of Verona), Christian Joppi (University of Verona), Andrea Giachetti (University of Verona), Fabio Pellacini (Sapienza University of Rome), Marco Cristani (University of Verona)

Element-based texture is a kind of texture formed by nameable elements, the texels, distributed according to specific statistical distributions; it is of primary importance in many sectors, namely textile, fashion and interior design industry. State-of-the art texture descriptors fail to properly characterize element-based texture, so we present Texel-Att to fill this gap. Texel-Att is the first fine-grained, attribute-based representation and classification framework for element-based textures. It first individuates texels, characterizing them with individual attributes; subsequently, texels are grouped and characterized through layout attributes, which give the Texel-Att representation. Texels are detected by a Mask-RCNN, trained on a brand-new element-based texture dataset, ElBa, containing 30K texture images with 3M fully-annotated texels. Examples of individual and layout attributes are exhibited to give a glimpse on the level of achievable graininess. In the experiments, we present detection results to show that texels can be precisely individuated, even on textures “in the wild”; to this sake, we individuate the elementbased classes of the Describable Texture Dataset (DTD), where almost 900K texels have been manually annotated, leading to the Element-based DTD (E-DTD). Subsequently, classification and ranking results demonstrate the expressivity of Texel-Att on ElBa and E-DTD, overcoming the alternative features and relative attributes, doubling the best performance in some cases; finally, we report interactive search results on ElBa and E-DTD: with Texel-Att on the E-DTD dataset we are able to individuate within 10 iterations the desired texture in the 90% of cases, against the 71% obtained with a combination of the finest existing attributes so far. Dataset and code is available at \url{https://github.com/godimarcovr/Texel-Att}.


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title={Texel-Att: Representing and Classifying Element-Based Textures by Attributes},
author={Marco Godi and Christian Joppi and Andrea Giachetti and Fabio Pellacini and Marco Cristani},
booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
publisher={BMVA Press},
editor={Kirill Sidorov and Yulia Hicks},