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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 32

Facial Landmarks Detection by Self-Iterative Regression Based Landmarks-Attention Network

March 15, 2023

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Published Date: 2018-02-08

Registration: ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)

Copyright: Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.

Authors

Tao Hu

University of Chinese Academy of Sciences


Honggang Qi

University of Chinese Academy of Sciences


Jizheng Xu

Microsoft Research Asia, Beijing


Qingming Huang

University of Chinese Academy of Sciences


DOI:

10.1609/aaai.v32i1.12275


Abstract:

Cascaded Regression (CR) based methods have been proposed to solve facial landmarks detection problem, which learn a series of descent directions by multiple cascaded regressors separately trained in coarse and fine stages. They outperform the traditional gradient descent based methods in both accuracy and running speed. However, cascaded regression is not robust enough because each regressor's training data comes from the output of previous regressor. Moreover, training multiple regressors requires lots of computing resources, especially for deep learning based methods. In this paper, we develop a Self-Iterative Regression (SIR) framework to improve the model efficiency. Only one self-iterative regressor is trained to learn the descent directions for samples from coarse stages to fine stages, and parameters are iteratively updated by the same regressor. Specifically, we proposed Landmarks-Attention Network (LAN) as our regressor, which concurrently learns features around each landmark and obtains the holistic location increment. By doing so, not only the rest of regressors are removed to simplify the training process, but the number of model parameters is significantly decreased. The experiments demonstrate that with only 3.72M model parameters, our proposed method achieves the state-of-the-art performance.

Topics: AAAI

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HOW TO CITE:

Tao Hu||Honggang Qi||Jizheng Xu||Qingming Huang Facial Landmarks Detection by Self-Iterative Regression Based Landmarks-Attention Network Proceedings of the AAAI Conference on Artificial Intelligence, 32 (2018) .

Tao Hu||Honggang Qi||Jizheng Xu||Qingming Huang Facial Landmarks Detection by Self-Iterative Regression Based Landmarks-Attention Network AAAI 2018, .

Tao Hu||Honggang Qi||Jizheng Xu||Qingming Huang (2018). Facial Landmarks Detection by Self-Iterative Regression Based Landmarks-Attention Network. Proceedings of the AAAI Conference on Artificial Intelligence, 32, .

Tao Hu||Honggang Qi||Jizheng Xu||Qingming Huang. Facial Landmarks Detection by Self-Iterative Regression Based Landmarks-Attention Network. Proceedings of the AAAI Conference on Artificial Intelligence, 32 2018 p..

Tao Hu||Honggang Qi||Jizheng Xu||Qingming Huang. 2018. Facial Landmarks Detection by Self-Iterative Regression Based Landmarks-Attention Network. "Proceedings of the AAAI Conference on Artificial Intelligence, 32". .

Tao Hu||Honggang Qi||Jizheng Xu||Qingming Huang. (2018) "Facial Landmarks Detection by Self-Iterative Regression Based Landmarks-Attention Network", Proceedings of the AAAI Conference on Artificial Intelligence, 32, p.

Tao Hu||Honggang Qi||Jizheng Xu||Qingming Huang, "Facial Landmarks Detection by Self-Iterative Regression Based Landmarks-Attention Network", AAAI, p., 2018.

Tao Hu||Honggang Qi||Jizheng Xu||Qingming Huang. "Facial Landmarks Detection by Self-Iterative Regression Based Landmarks-Attention Network". Proceedings of the AAAI Conference on Artificial Intelligence, 32, 2018, p..

Tao Hu||Honggang Qi||Jizheng Xu||Qingming Huang. "Facial Landmarks Detection by Self-Iterative Regression Based Landmarks-Attention Network". Proceedings of the AAAI Conference on Artificial Intelligence, 32, (2018): .

Tao Hu||Honggang Qi||Jizheng Xu||Qingming Huang. Facial Landmarks Detection by Self-Iterative Regression Based Landmarks-Attention Network. AAAI[Internet]. 2018[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
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Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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