1 code implementation • 30 Aug 2023 • Yi Ding, Su Zhang, Chuangao Tang, Cuntai Guan
A natural method is to learn the temporal dynamic patterns.
no code implementations • 22 Oct 2022 • Cheng Lu, Wenming Zheng, Hailun Lian, Yuan Zong, Chuangao Tang, Sunan Li, Yan Zhao
The F-Encoder and T-Encoder model the correlations within frequency bands and time frames, respectively, and they are embedded into a time-frequency joint learning strategy to obtain the time-frequency patterns for speech emotions.
no code implementations • 18 Sep 2022 • Xiaolin Xu, Yuan Zong, Wenming Zheng, Yang Li, Chuangao Tang, Xingxun Jiang, Haolin Jiang
In this paper, we present a large-scale, multi-source, and unconstrained database called SDFE-LV for spotting the onset and offset frames of a complete dynamic facial expression from long videos, which is known as the topic of dynamic facial expression spotting (DFES) and a vital prior step for lots of facial expression analysis tasks.
no code implementations • 13 Aug 2020 • Xingxun Jiang, Yuan Zong, Wenming Zheng, Chuangao Tang, Wanchuang Xia, Cheng Lu, Jiateng Liu
Experimental results show that DFEW is a well-designed and challenging database, and the proposed EC-STFL can promisingly improve the performance of existing spatiotemporal deep neural networks in coping with the problem of dynamic FER in the wild.
Ranked #17 on Dynamic Facial Expression Recognition on DFEW
Dynamic Facial Expression Recognition Facial Expression Recognition +1
no code implementations • 19 Dec 2018 • Yuan Zong, Tong Zhang, Wenming Zheng, Xiaopeng Hong, Chuangao Tang, Zhen Cui, Guoying Zhao
Cross-database micro-expression recognition (CDMER) is one of recently emerging and interesting problem in micro-expression analysis.