A human pose estimation network based on YOLOv8 framework with efficient multi-scale receptive field and expanded feature pyramid network
Abstract Deep neural networks are used to accurately detect, estimate, and predict human body poses in images or videos through deep learning-based human pose estimation. However, traditional multi-person pose estimation methods face challenges due to partial occlusions and overlaps between multiple...
Saved in:
| Main Authors: | Shaobin Cai, Han Xu, Wanchen Cai, Yuchang Mo, Liansuo Wei |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-00259-0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Research on Lightweight Model of Multi-person Pose Estimation Based on Improved YOLOv8s-Pose
by: FU Yu, GAO Shuhui
Published: (2025-03-01) -
6D Pose Estimation Algorithm Based on Improved YOLOv5 With Asymptotic Feature Pyramid Network and Attention Mechanism
by: Yan Zhang, et al.
Published: (2025-01-01) -
Enhanced Pose Estimation for Badminton Players via Improved YOLOv8-Pose with Efficient Local Attention
by: Yijian Wu, et al.
Published: (2025-07-01) -
Feature pyramid attention network for audio‐visual scene classification
by: Liguang Zhou, et al.
Published: (2025-04-01) -
Vibrator Rack Pose Estimation for Monitoring the Vibration Quality of Concrete Using Improved YOLOv8-Pose and Vanishing Points
by: Bingyu Ren, et al.
Published: (2024-10-01)