HRNET-Posenet: Pose Estimation
HRNet-PoseNet is a pose estimation model based on the HRNet (High-Resolution Network) architecture, specifically designed for human keypoint detection and pose estimation tasks. HRNet-PoseNet maintains high-resolution feature representations throughout the network, while processing features in parallel across multiple resolutions to capture both global and local information of the human body. This design enables high-precision keypoint localization, retaining high-quality pose estimation even in complex scenarios. HRNet-PoseNet performs exceptionally well in various pose estimation tasks and is widely applied in fields like sports analysis, action recognition, virtual reality, and human-computer interaction, providing robust support for real-time and precise pose estimation.
Source model
- Input shape: 256x192
- Number of parameters: 28.5M
- Model size: 108.94M
- Output shape: 1x17x64x48
Source model repository: HRNET-Posenet
Performance Reference
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Inference & Model Conversion
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License
Source Model: MIT
Deployable Model: APLUX-MODEL-FARM-LICENSE