Ghost-HRNet: a lightweight high-resolution network for efficient human pose estimation with enhanced multi-scale feature fusion

• Published in: Pattern analysis and applications : PAA Vol. 28; no. 2
• Main Authors: Zheng, Xiaoyu, Zhuang, Liping, Chen, Dewang
• Format: Journal Article
• Language: English
• Published: London Springer London 01.06.2025; Springer Nature B.V
• Subjects: Computer Science; Computer vision; Feature extraction; High resolution; Modules; Original Article; Parameters; Pattern Recognition; Pose estimation; Real time; Virtual reality; Human pose estimation; Ghost module; Depthwise separable convolution; Lightweight network; High-resolution networks

Human pose estimation (HPE) is a critical task in computer vision, with applications spanning human-computer interaction, intelligent surveillance, behavior analysis, virtual reality, and medical diagnosis. However, existing high-resolution networks (HRNet) face challenges due to their large paramet...