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Deforming autoencoders: Unsupervised disentangling of shape and appearance

Shu, Z; Sahasrabudhe, M; Alp Güler, R; Samaras, D; Paragios, N; Kokkinos, I; (2018) Deforming autoencoders: Unsupervised disentangling of shape and appearance. In: Computer Vision – ECCV 2018. (pp. pp. 664-680). Springer: Cham, Switzerland. Green open access

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Abstract

In this work we introduce Deforming Autoencoders, a generative model for images that disentangles shape from appearance in an unsupervised manner. As in the deformable template paradigm, shape is represented as a deformation between a canonical coordinate system (‘template’) and an observed image, while appearance is modeled in deformation-invariant, template coordinates. We introduce novel techniques that allow this approach to be deployed in the setting of autoencoders and show that this method can be used for unsupervised group-wise image alignment. We show experiments with expression morphing in humans, hands, and digits, face manipulation, such as shape and appearance interpolation, as well as unsupervised landmark localization. We also achieve a more powerful form of unsupervised disentangling in template coordinates, that successfully decomposes face images into shading and albedo, allowing us to further manipulate face images.

Type: Proceedings paper
Title: Deforming autoencoders: Unsupervised disentangling of shape and appearance
Event: ECCV: European Conference on Computer Vision
ISBN-13: 9783030012489
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-030-01249-6_40
Publisher version: https://doi.org/10.1007/978-3-030-01249-6_40
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10074873
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