no code implementations • 2 Nov 2015 • Xiaobai Li, Xiaopeng Hong, Antti Moilanen, Xiaohua Huang, Tomas Pfister, Guoying Zhao, Matti Pietikäinen
For ME recognition, the performance of previous studies is low.
no code implementations • 7 Aug 2016 • Xiaohua Huang, Su-Jing Wang, Xin Liu, Guoying Zhao, Xiaoyi Feng, Matti Pietikainen
For increasing the discrimination of micro-expressions, we propose a new feature selection based on Laplacian method to extract the discriminative information for facial micro-expression recognition.
no code implementations • 12 Sep 2016 • Zhiyuan Zha, Xin Liu, Ziheng Zhou, Xiaohua Huang, Jingang Shi, Zhenhong Shang, Lan Tang, Yechao Bai, Qiong Wang, Xinggan Zhang
Group sparsity has shown great potential in various low-level vision tasks (e. g, image denoising, deblurring and inpainting).
no code implementations • 12 Oct 2016 • Xiaohua Huang, Abhinav Dhall, Xin Liu, Guoying Zhao, Jingang Shi, Roland Goecke, Matti Pietikainen
We fuse face, upperbody and scene information for robustness of GER against the challenging environments.
no code implementations • 28 Nov 2016 • Zhiyuan Zha, Xin Liu, Xiaohua Huang, Henglin Shi, Yingyue Xu, Qiong Wang, Lan Tang, Xinggan Zhang
Then, we prove that group-based sparse coding is equivalent to the rank minimization problem, and thus the sparse coefficient of each group is measured by estimating the singular values of each group.
no code implementations • 26 Jul 2017 • Yuan Zong, Xiaohua Huang, Wenming Zheng, Zhen Cui, Guoying Zhao
In this paper, we investigate the cross-database micro-expression recognition problem, where the training and testing samples are from two different micro-expression databases.
no code implementations • 11 Jul 2019 • Yante Li, Xiaohua Huang, Guoying Zhao
In this paper, we focus on AU detection in micro-expressions.
no code implementations • 13 Jan 2021 • Ling Zhou, Qirong Mao, Xiaohua Huang, Feifei Zhang, Zhihong Zhang
It aims to obtain salient and discriminative features for specific expressions and also predict expression by fusing the expression-specific features.
Micro Expression Recognition Micro-Expression Recognition +1
no code implementations • 13 Jul 2021 • Qirong Mao, Ling Zhou, Wenming Zheng, Xiuyan Shao, Xiaohua Huang
More specifically, the backbone network aims at extracting feature representations from different facial regions, RI module computing an adaptive weight from the region itself based on attention mechanism with respect to the unobstructedness and importance for suppressing the influence of occlusion, and RR module exploiting the progressive interactions among these regions by performing graph convolutions.
no code implementations • 13 Jul 2022 • Xiaoyu Yuan, Zhibo Zhang, Yabo Sun, Zekai Xue, Xiuyan Shao, Xiaohua Huang
This paper proposes a new database of Houma Alliance Book ancient handwritten characters and a multi-modal fusion method to recognize ancient handwritten characters.
no code implementations • 3 Aug 2022 • Xiang Yu, Zhe Geng, Xiaohua Huang, Qinglu Wang, Daiyin Zhu
In recent years, convolutional neural networks (CNNs) have shown great potential in synthetic aperture radar (SAR) target recognition.
no code implementations • 6 Oct 2023 • Qing Zhu, Qirong Mao, Jialin Zhang, Xiaohua Huang, Wenming Zheng
Group-level emotion recognition (GER) is an inseparable part of human behavior analysis, aiming to recognize an overall emotion in a multi-person scene.
no code implementations • 16 Oct 2023 • Ling Zhou, Mingpei Wang, Xiaohua Huang, Wenming Zheng, Qirong Mao, Guoying Zhao
Micro-expression recognition (MER) in low-resolution (LR) scenarios presents an important and complex challenge, particularly for practical applications such as group MER in crowded environments.