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Authors: Ali Zakir 1 ; Sartaj Salman 1 ; Gibran Benitez-Garcia 1 and Hiroki Takahashi 1 ; 2

Affiliations: 1 Department of Informatics, Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan ; 2 Artificial Intelligence Exploration/Meta-Networking Research Center, The University of Electro-Communications, Tokyo, Japan

Keyword(s): 2D Human Pose Estimation, EBA-PRNetCC, MLP, EBA, COCO Dataset.

Abstract: In the current era, 2D Human Pose Estimation has emerged as an essential component in advanced Computer Vision tasks, particularly for understanding human behaviors. While challenges such as occlusion and unfavorable lighting conditions persist, the advent of deep learning has significantly strengthened the efficacy of 2D HPE. Yet, traditional 2D heatmap methodologies face quantization errors and demand complex post-processing. Addressing this, we introduce the EBA-PRNetCC model, an innovative coordinate classification approach for 2D HPE, emphasizing improved prediction accuracy and optimized model parameters. Our EBA-PRNetCC model employs a modified ResNet34 framework. A key feature is its head, which includes a dual-layer Multi-Layer Perceptron augmented by the Mish activation function. This design not only improves pose estimation precision but also minimizes model parameters. Integrating the Efficient Bridge Attention Net further enriches feature extraction, granting the model d eep contextual insights. By enhancing pixel-level discretization, joint localization accuracy is improved. Comprehensive evaluations on the COCO dataset validate our model’s superior accuracy and computational efficiency performance compared to prevailing 2D HPE techniques. (More)

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Paper citation in several formats:
Zakir, A.; Salman, S.; Benitez-Garcia, G. and Takahashi, H. (2024). EBA-PRNetCC: An Efficient Bridge Attention-Integration PoseResNet for Coordinate Classification in 2D Human Pose Estimation. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-679-8; ISSN 2184-4321, SciTePress, pages 133-144. DOI: 10.5220/0012366300003660

@conference{visapp24,
author={Ali Zakir. and Sartaj Salman. and Gibran Benitez{-}Garcia. and Hiroki Takahashi.},
title={EBA-PRNetCC: An Efficient Bridge Attention-Integration PoseResNet for Coordinate Classification in 2D Human Pose Estimation},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2024},
pages={133-144},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012366300003660},
isbn={978-989-758-679-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - EBA-PRNetCC: An Efficient Bridge Attention-Integration PoseResNet for Coordinate Classification in 2D Human Pose Estimation
SN - 978-989-758-679-8
IS - 2184-4321
AU - Zakir, A.
AU - Salman, S.
AU - Benitez-Garcia, G.
AU - Takahashi, H.
PY - 2024
SP - 133
EP - 144
DO - 10.5220/0012366300003660
PB - SciTePress