Deep Filter Banks for Texture Recognition, Description, and Segmentation

Mircea Cimpoi, Subhransu Maji, Iasonas Kokkinos, Andrea Vedaldi
2016 International Journal of Computer Vision  
Visual textures have played a key role in image understanding because they convey important semantics of images, and because texture representations that pool local image descriptors in an orderless manner have had a tremendous impact in diverse applications. In this paper we make several contributions to texture understanding. First, instead of focusing on texture instance and material category recognition, we propose a human-interpretable vocabulary of texture attributes to describe common
more » ... ture patterns, complemented by a new describable texture dataset for benchmarking. Second, we look at the problem of recognizing materials and texture attributes in realistic imaging conditions, including when textures appear in clutter, developing corresponding benchmarks on top of the recently proposed OpenSurfaces dataset. Third, we revisit classic texture represenations, including bag-of-visual-words and the Fisher vectors, in the context of deep learning and show that these have excellent efficiency and generalization properties if the convolutional layers of a deep model are used as Communicated by
doi:10.1007/s11263-015-0872-3 pmid:27471340 pmcid:PMC4946812 fatcat:z7sz65gi5nevbgsh2tt3kzdnzi