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OpenPose-Plus: Pose Estimation in the Wild

OpenPose is the state-of-the-art pose estimation algorithm.In its Caffe codebase,data augmentation, training, and neural networks are most hard-coded. They are difficultto be customised. In addition,key performance features such as embedded platform supports and parallel GPU training are missing.All these limitations makes OpenPose, in these days, hard tobe deployed in the wild. To resolve this, we develop OpenPose-Plus, a high-performance yet flexible pose estimation framework that offers many powerful features:

• Flexible combination of standard training dataset with your own custom labelled data.
• Customisable data augmentation pipeline without compromising performance
• Deployment on embedded platforms using TensorRT
• Switchable neural networks (e.g., changing VGG to MobileNet for minimal memory consumption)
• High-performance training using multiple GPUs