Seeking Salient Facial Regions for Cross-Database Micro-Expression Recognition

1 code implementation • 30 Nov 2021 • Xingxun Jiang, Yuan Zong, Wenming Zheng, Jiateng Liu, Mengting Wei

To solve these problems, this paper proposes a novel Transfer Group Sparse Regression method, namely TGSR, which aims to 1) optimize the measurement and better alleviate the difference between the source and target databases, and 2) highlight the valid facial regions to enhance extracted features, by the operation of selecting the group features from the raw face feature, where each region is associated with a group of raw face feature, i. e., the salient facial region selection.

Domain Adaptation Micro Expression Recognition +2

DFEW: A Large-Scale Database for Recognizing Dynamic Facial Expressions in the Wild

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.

Dynamic Facial Expression Recognition Facial Expression Recognition +1

SDFE-LV: A Large-Scale, Multi-Source, and Unconstrained Database for Spotting Dynamic Facial Expressions in Long Videos

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.