2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDMLR-APPL-IP-7.1
Paper Title DEEP ACTIVE LEARNING FOR HUMAN POSE ESTIMATION VIA CONSISTENCY WEIGHTED CORE-SET APPROACH
Authors Wuqiang Zhang, Zijie Guo, Rong Zhi, Baofeng Wang, Daimler Greater China, China
SessionMLR-APPL-IP-7: Machine learning for image processing 7
LocationArea E
Session Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Poster
Topic Applications of Machine Learning: Machine learning for image processing
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Aiming to develop an annotation-efficient algorithm by selecting the most informative samples to be labeled for human pose estimation, we propose a novel active learning approach that generalized the standard core-set approach by dynamically incorporating the uncertainty and representativeness cues. Based on our designed assignment cost that consists of fast spatial consistency and domain-shift scaled distance, our method proposed an adaptive information measurement as data selection criterion. Extensive experiments conducted on two network architectures and various datasets demonstrate the effectiveness and superiority of our proposed approach in comparison with other state-of-the-art methods.