Toward a Universal Model for Shape From Texture

Dor Verbin, Todd Zickler; The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 422-430

Abstract


We consider the shape from texture problem, where the input is a single image of a curved, textured surface, and the texture and shape are both a priori unknown. We formulate this task as a three-player game between a shape process, a texture process, and a discriminator. The discriminator adapts a set of non-linear filters to try to distinguish image patches created by the texture process from those created by the shape process, while the shape and texture processes try to create image patches that are indistinguishable from those of the other. An equilibrium of this game yields two things: an estimate of the 2.5D surface from the shape process, and a stochastic texture synthesis model from the texture process. Experiments show that this approach is robust to common non-idealities such as shading, gloss, and clutter. We also find that it succeeds for a wide variety of texture types, including both periodic textures and those composed of isolated textons, which have previously required distinct and specialized processing.

Related Material


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[bibtex]
@InProceedings{Verbin_2020_CVPR,
author = {Verbin, Dor and Zickler, Todd},
title = {Toward a Universal Model for Shape From Texture},
booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}