期刊论文

Shao, WZ

英文

Knowledge-Based Systems

0950-7051

2024

292

111595

10.1016/j.knosys.2024.111595

This scientific work is supported by General Program of Natural Science Foundation of Hunan Province, China (2021JJ31164), Key Program of Science Research Foundation of Education Department of Hunan Province, China (22A0195), Teaching Reform Research Program of Education Department of Hunan Province, China (HNJG-20230471).

本校为第一且通讯机构

Recently, emotion recognition from facial expressions has achieved unprecedented accuracy with the development of deep learning. Despite this progress, most existing emotion recognition methods are supervised and thus require extensive annotation. This issue is particularly pronounced in continuous domain datasets where annotation costs are very high. Furthermore, discrete domain datasets containing specific poses are too uniform to reflect complex and actual emotions. Existing methods that employ classification loss pay little attention to ima...