Optimizing Human Pose Estimation Using a Simplified UNet Architecture: An Experimental Analysis on Depth and Width Parameters

Human pose estimation (HPE) is a significant problem in the field of computer vision, with wide applications in action recognition, intelligent surveillance, and other areas. With the development of deep learning, the accuracy of pose estimation has significantly improved. However, high-precision po

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.4108/eai.21-11-2024.2354631
Primary Topic
Human Pose and Action Recognition
Type
article
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article

Optimizing Human Pose Estimation Using a Simplified UNet Architecture: An Experimental Analysis on Depth and Width Parameters

Shenghao Ren
Human Pose and Action Recognition
article

Optimizing Human Pose Estimation Using a Simplified UNet Architecture: An Experimental Analysis on Depth and Width Parameters

Shenghao Ren
article en

Abstract

Human pose estimation (HPE) is a significant problem in the field of computer vision, with wide applications in action recognition, intelligent surveillance, and other areas. With the development of deep learning, the accuracy of pose estimation has significantly improved. However, high-precision po

Openalex Percentile: Top 96%
Human Pose and Action Recognition
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Optimizing Human Pose Estimation Using a Simplified UNet Architecture: An Experimental Analysis on Depth and Width Parameters — Shenghao Ren · (2025) | TGRS Research Map | TGRS