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Alejandro Newell, Kaiyu Yang, and Jia Deng, Stacked Hourglass Networks for Human Pose Estimation, arXiv:1603.06937, 2016. A pretrained model is available on the project site . You can use the option -loadModel path/to/model to try fine-tuning.
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Mar 22, 2016 · Stacked Hourglass Networks for Human Pose Estimation. Alejandro Newell, Kaiyu Yang, Jia Deng. This work introduces a novel convolutional network architecture for the task of human pose estimation. Features are processed across all scales and consolidated to best capture the various spatial relationships associated with the body.
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Mar 22, 2016 · 2021. TLDR. A novel graph convolutional network architecture, Graph Stacked Hourglass Networks, for 2D-to-3D human pose estimation tasks, in which graph-structured features are processed across three different scales of human skeletal representations, which enables the model to learn both local and global feature representations. Expand.
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