no code implementations • CVPR 2018 • Feifei Zhang, Tianzhu Zhang, Qirong Mao, Changsheng Xu
First, the encoder-decoder structure of the generator can learn a generative and discriminative identity representation for face images.
Facial Expression Recognition Facial Expression Recognition (FER) +2
5 code implementations • Interspeech 2020 • Jingjing Chen, Qirong Mao, Dong Liu
By introduces a improved transformer, elements in speech sequences can interact directly, which enables DPTNet can model for the speech sequences with direct context-awareness.
Ranked #15 on Speech Separation on WSJ0-2mix
Speech Separation Audio and Speech Processing Sound
no code implementations • 24 Dec 2020 • Ling Zhou, Qirong Mao, Ming Dong
Specifically, we propose two new strategies in our AU detection module for more effective AU feature learning: the attention mechanism and the balanced detection loss function.
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.
1 code implementation • 3 Sep 2022 • Zhongchen Ma, Lisha Li, Qirong Mao, Songcan Chen
However, these CL methods fail to be directly adapted to multi-label image classification due to the difficulty in defining the positive and negative instances to contrast a given anchor image in multi-label scenario, let the label missing one alone, implying that borrowing a commonly-used way from contrastive multi-class learning to define them will incur a lot of false negative instances unfavorable for learning.
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.