基于广义高效层聚合网络和共享卷积的卡通角色面部检测  

Cartoon Character Face Detection Based on Generalized Efficient Layer Aggregation Network and Shared Convolution

作　　者：闫博文 刘永泽 夏海东 宋晓强 YAN Bo-Wen;LIU Yong-Ze;XIA Hai-Dong;SONG Xiao-Qiang(School of Information Science and Technology,Shijiazhuang Tiedao University,Shijiazhuang 050043,China)

机构地区：[1]石家庄铁道大学信息科学与技术学院,石家庄050043

出　　处：《计算机系统应用》2025年第2期154-164,共11页Computer Systems & Applications

基　　金：河北省自然科学基金面上项目(F2019210253)。

摘　　要：卡通角色面部检测是一项比人脸检测更具挑战性的任务,它涉及许多困难的场景.针对卡通角色面部间存在巨大差异的特点,本文提出了一种卡通角色面部检测算法,命名为YOLO-DEL.首先,基于GELAN融合BDD设计了DBBNCSPELAN模块,旨在减小模型体积的同时增强检测性能.接下来,引入一种称为ELA的多尺度注意机制,用于改善SPPF结构,增强主干模型的特征提取能力.最后,设计了新的共享卷积检测头,使网络更轻便.同时也用Shape-IoU代替原CIoU损失函数,提升模型的收敛效率.在iCartoonFace数据集上进行实验,通过消融实验验证得到的模型,并将其与YOLOv3-tiny、YOLOv5n和YOLOv6等模型进行比较.改进模型YOLO-DEL的mAP达到90.3%,比YOLOv8提高了1.2%,参数量为1.69M,与YOLOv8相比参数量降低47%,GFLOPs降低44%.实验表明,本文方法能有效提高卡通角色面部的检测精度,同时缩小网络模型的大小,验证本文方法的有效性.Cartoon character face detection is more challenging than face detection because it involves many difficult scenarios.Given the huge differences between different cartoon characters’faces,this study proposes a cartoon character face detection algorithm,named YOLOv8-DEL.Firstly,the DBBNCSPELAN module is designed based on GELAN fusion BDD to reduce model size and enhance detection performance.Next,a multi-scale attention mechanism called ELA is introduced to improve the SPPF structure and enhance the feature extraction ability of the backbone model.Finally,a new detection head for shared convolution is designed to make the network lighter.At the same time,the original CIoU loss function is replaced by Shape-IoU to improve the convergence efficiency of the model.Experiments are carried out on the iCartoonFace dataset,and ablation experiments are carried out to verify the proposed model.Besides,the proposed model is compared with the YOLOv3-tiny,YOLOv5n,and YOLOv6 models.The mAP of the improved model YOLO-DEL reaches 90.3%,1.2%higher than that of YOLOv8.The parameters amount is 1.69M,47%lower than that of YOLOv8.The GFLOPs value is 44%lower than that of YOLOv8.Experimental results show that the proposed method effectively improves cartoon character face detection precision while compressing the network model’s size.Thus,the proposed method has proved to be effective.

关 键 词：目标检测 卡通面部 GELAN 注意力机制 YOLOv8 共享卷积 

分 类 号：J218.7[艺术—美术] TP391.41[自动化与计算机技术—计算机应用技术]