计算机应用研究2026，Vol.43Issue(8)：2278-2285,8.DOI:10.19734/j.issn.1001-3695.2025.12.0513
基于双通路融合网络的用户视频情感识别
Emotion recognition in user-generated video based on dual-path fusion network
摘要
Abstract
Facing challenges from dynamic content,diverse themes,and sparse emotion distributions in user-generated videos,this paper developed a dual-path fusion network(DPFNet).The core of DPFNet was a dual-path encoding structure with attention mechanisms.The main path modeled temporal dependencies of visual embeddings,while an auxiliary path introduced emotional auxiliary text to reconstruct and constrain visual features for adaptation to diverse themes.Then a dual-path decoder processed both paths in parallel to capture emotion-relevant visual content.Finally,a dynamic gating mechanism adaptively fused the decoded features to suppress task-irrelevant interference.Experiments on two public datasets show that DPFNet achieves classification accuracies of 60.2％and 63.7％,respectively.DPFNet demonstrates more efficient recognition using only visual modality input while maintaining comparable classification performance,significantly reducing model complexity and computational costs.关键词
用户视频/视频情感识别/视觉-语言模型/辅助文本嵌入/语义查询向量/双路解码器/动态门控融合Key words
user-generated video/video emotion recognition/vision-language model/auxiliary text embedding/semantic querying vector/dual-path decoder/dynamic gating fusion分类
信息技术与安全科学引用本文复制引用
刘玉杰,董振阳..基于双通路融合网络的用户视频情感识别[J].计算机应用研究,2026,43(8):2278-2285,8.基金项目
国家重点研发计划资助项目(2019YFF03018000) （2019YFF03018000）
国家自然科学基金资助项目(61379106) （61379106）
山东省自然科学基金资助项目(ZR2013FM036,ZR2015FM011) （ZR2013FM036,ZR2015FM011）
