Simultaneous Estimation of Facial Landmark and Attributes with Separation Multi-task Networks

Ryo Matsui, Takayoshi Yamashita, Hironobu Fujiyoshi

Abstract

Multi-task learning is a machine learning approach in which multiple tasks are solved simultaneously. This approach can improve learning efficiency and prediction accuracy for the task-specific models. Furthermore, it has been used successfully across various applications such as natural language processing and computer vision. Multi-task learning consists of shared layers and task-specific layers. The shared layers extract common low-level features for all tasks, the task-specific layers diverge from the shared layers and extract specific high-level features for each task. Hence, conventional multi-task learning architecture cannot extract the low-level task-specific feature. In this work, we propose Separation Multi-task Networks, a novel multi-task learning architecture that extracts shared features and task-specific features in various layers. Our proposed method extracts low- to high-level task-specific features by feeding task-specific layers in parallel to each shared layer. Moreover, we employ channel-wise convolution when concatenating feature maps of shared layers and task-specific layers. This convolution allows concatenation even if layers have a different number of channels of feature maps. In experiments on CelebA dataset, our proposed method outperformed conventional methods at facial landmark detection and facial attribute estimation.

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Paper Citation


in Harvard Style

Matsui R., Yamashita T. and Fujiyoshi H. (2019). Simultaneous Estimation of Facial Landmark and Attributes with Separation Multi-task Networks.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, ISBN 978-989-758-354-4, pages 265-272. DOI: 10.5220/0007342602650272


in Bibtex Style

@conference{visapp19,
author={Ryo Matsui and Takayoshi Yamashita and Hironobu Fujiyoshi},
title={Simultaneous Estimation of Facial Landmark and Attributes with Separation Multi-task Networks},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,},
year={2019},
pages={265-272},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007342602650272},
isbn={978-989-758-354-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP,
TI - Simultaneous Estimation of Facial Landmark and Attributes with Separation Multi-task Networks
SN - 978-989-758-354-4
AU - Matsui R.
AU - Yamashita T.
AU - Fujiyoshi H.
PY - 2019
SP - 265
EP - 272
DO - 10.5220/0007342602650272