Collection
SI: Human Pose Estimation and Its Applications
- Submission status
- Closed
Human pose estimation is an important task in computer vision because it not only benefits other vision tasks like action recognition, person re-identification and virtual try-on but also facilitates applications in real-world domains such as robotics, healthcare, sports, and retail. An effective and efficient human pose estimation system can help robots learn skills from demonstrations, help physical therapists diagnose and rehabilitate patients, help sports analysts or coaches track and train athletes, and help retailers build employee-free stores.
Thanks to the development of deep learning and large-scale datasets, the performance of state-of-the-art human pose estimation approaches has drastically improved in recent years, and they can estimate postures in daily activities and some sports accurately. However, several challenges still exist. For example, (1) it is challenging to estimate postures which rarely or never occur in the training data; (2) it is difficult to handle complex scenarios such as crowded people, motion blur, low-light conditions, and occlusions; (3) it is desirable to establish efficient models which can estimate human poses in real time or on low-power devices; (4) it is exciting to create new applications of human pose estimation that can benefit society or transform industry.
Editors
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Wei Tang
University of Illinois Chicago, USA
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Zhou Ren
Amazon AWS, USA
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**gdong Wang
Baidu, China
Articles (8 in this collection)
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Pakistan sign language recognition: leveraging deep learning models with limited dataset
Authors
- Hafiz Muhammad Hamza
- Aamir Wali
- Content type: Original Paper
- Published: 17 July 2023
- Article: 71
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Automatic apraxia detection using deep convolutional neural networks and similarity methods
Authors (first, second and last of 6)
- Cristina Vicedo
- Alicia Nieto-Reyes
- José Luis Montaña
- Content type: Original Paper
- Open Access
- Published: 24 June 2023
- Article: 60
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Crowded pose-guided multi-task learning for instance-level human parsing
Authors (first, second and last of 5)
- Yong Wei
- Li Liu
- Wei Peng
- Content type: Original Paper
- Published: 05 May 2023
- Article: 46
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Wide-baseline multi-camera calibration from a room filled with people
Authors (first, second and last of 4)
- S. Dehaeck
- C. Domken
- G. Abedrabbo
- Content type: Original Paper
- Published: 28 April 2023
- Article: 45
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Human skeleton behavior recognition model based on multi-object pose estimation with spatiotemporal semantics
Authors (first, second and last of 4)
- Jiaji Liu
- **aofang Mu
- Hao Li
- Content type: Original Paper
- Open Access
- Published: 28 April 2023
- Article: 44
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ICE-GCN: An interactional channel excitation-enhanced graph convolutional network for skeleton-based action recognition
Authors (first, second and last of 6)
- Shuxi Wang
- Jiahui Pan
- Chengju Zhou
- Content type: Original Paper
- Open Access
- Published: 05 April 2023
- Article: 40
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Human pose estimation based on lightweight basicblock
Authors (first, second and last of 4)
- Yan** Li
- Ruyi Liu
- Rui Wang
- Content type: Special Issue Paper
- Published: 13 November 2022
- Article: 3