Welcome to the PocketPose Model Zoo, your ultimate resource for pre-trained models designed for fast, accurate, and efficient human pose estimation across a variety of frameworks and keypoint formats. Whether youβre building real-time applications or conducting cutting-edge research, our models provide high-performance solutions without the hassle of training from scratch.
For minimal setup with automatic selection of the best model for your use case, visit our Get Started page.
For Researchers & Developers: Alongside the latest high-performance pose estimation models, we provide access to legacy models that played a pivotal role in shaping the field. These older models are ideal for comparative research, benchmarking, and academic exploration.
Use our interactive Model Explorer below to filter and discover all available models in the PocketPose Model Zoo.
Name | Input Size | Keypoints | Size (MB) | Accuracy* | Speed (FPS)** | Backend | Source | License |
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RTMW (2024) Top-down | CSPNeXt | Coordinate Classification |
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RTMW-m | 256x192x3 | COCO_WHOLEBODY | ONNX | MMPose: Code · Weights | Apache-2.0 | |||
RTMPose (2023) Top-down | CSPNeXt | Coordinate Classification |
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RTMPose-t | 256x192x3 | COCO | ONNX | MMDeploy: Code · Weights | Apache-2.0 | |||
RTMPose-s | 256x192x3 | COCO | ONNX | MMDeploy: Code · Weights | Apache-2.0 | |||
RTMPose-m | 256x192x3 | COCO | ONNX | MMDeploy: Code · Weights | Apache-2.0 | |||
RTMPose-l | 256x192x3 | COCO | ONNX | MMDeploy: Code · Weights | Apache-2.0 | |||
SimCC (2021) Top-down | ResNet, MobileNetV2, ViPNAS-MBV3 | Coordinate Classification |
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SimCC-mbv2 | 256x192x3 | COCO | ONNX | MMDeploy: Code · Weights | Apache-2.0 | |||
SimCC-ViPNAS-MBV3 | 256x192x3 | COCO | ONNX | MMDeploy: Code · Weights | Apache-2.0 | |||
SimCC-ResNet50 | 256x192x3 | COCO | ONNX | MMDeploy: Code · Weights | Apache-2.0 | |||
MoveNet (2021) Bottom-up | MobileNetV2 + FPN | Person Center, Keypoint Heatmap, Keypoint Regression, and Offset Heads |
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MoveNet Lightning | 192x192x3 | COCO | TFLITE | TensorFlow Hub: Weights | Apache-2.0 | |||
MoveNet Lightning FP16 | 192x192x3 | COCO | TFLITE | TensorFlow Hub: Weights | Apache-2.0 | |||
MoveNet Lightning INT8 | 192x192x3 | COCO | TFLITE | TensorFlow Hub: Weights | Apache-2.0 | |||
MoveNet Thunder | 256x256x3 | COCO | TFLITE | TensorFlow Hub: Weights | Apache-2.0 | |||
MoveNet Thunder FP16 | 256x256x3 | COCO | TFLITE | TensorFlow Hub: Weights | Apache-2.0 | |||
MoveNet Thunder Int8 | 256x256x3 | COCO | TFLITE | TensorFlow Hub: Weights | Apache-2.0 | |||
EfficientPose (2020) Bottom-up | EfficientNet | Heatmap and Part Affinity Fields Regression |
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EfficientPose-RT | 224x224x3 | MPII | TFLITE | Official Repo: Code · Weights | Apache-2.0 | |||
EfficientPose-RT-Lite | 224x224x3 | MPII | TFLITE | Official Repo: Code · Weights | Apache-2.0 | |||
EfficientPose-I | 256x256x3 | MPII | TFLITE | Official Repo: Code · Weights | Apache-2.0 | |||
EfficientPose-I-Lite | 256x256x3 | MPII | TFLITE | Official Repo: Code · Weights | Apache-2.0 | |||
EfficientPose-II | 368x368x3 | MPII | TFLITE | Official Repo: Code · Weights | Apache-2.0 | |||
EfficientPose-II-Lite | 368x368x3 | MPII | TFLITE | Official Repo: Code · Weights | Apache-2.0 | |||
EfficientPose-III | 480x480x3 | MPII | TFLITE | Official Repo: Code · Weights | Apache-2.0 | |||
EfficientPose-IV | 600x600x3 | MPII | TFLITE | Official Repo: Code · Weights | Apache-2.0 | |||
EfficientPose with NAS (2020) Top-down | NAS-Optimized Backbone | Heatmap Regression |
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NASNet-A (COCO) | 256x192x3 | COCO | TFLITE | Official Repo: Code · Weights | Unspecified | |||
NASNet-B (COCO) | 256x192x3 | COCO | TFLITE | Official Repo: Code · Weights | Unspecified | |||
NASNet-B (MPII) | 256x256x3 | MPII | TFLITE | Official Repo: Code · Weights | Unspecified | |||
NASNet-C (COCO) | 256x192x3 | COCO | TFLITE | Official Repo: Code · Weights | Unspecified | |||
NASNet-C (MPII) | 256x256x3 | MPII | TFLITE | Official Repo: Code · Weights | Unspecified | |||
BlazePose (2020) Top-down | 1.5-Stage Tiny Hourglass | Direct Keypoint Regression |
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BlazePose-Lite | 256x256x3 | BLAZEPOSE | MEDIAPIPE | MediaPipe: Code · Weights | Apache-2.0 | |||
BlazePose-Full | 256x256x3 | BLAZEPOSE | MEDIAPIPE | MediaPipe: Code · Weights | Apache-2.0 | |||
BlazePose-Heavy | 256x256x3 | BLAZEPOSE | MEDIAPIPE | MediaPipe: Code · Weights | Apache-2.0 | |||
Lightweight Pose Network (2019) Top-down | ResNet + Lightweight Bottleneck Blocks | Heatmap Regression |
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LPN-50 (COCO) | 256x192x3 | COCO | ONNX | Official Repo: Code · Weights | MIT | |||
LPN-101 (COCO) | 256x192x3 | COCO | ONNX | Official Repo: Code · Weights | MIT | |||
LPN-152 (COCO) | 256x192x3 | COCO | ONNX | Official Repo: Code · Weights | MIT | |||
LPN-50 (MPII) | 256x256x3 | MPII | ONNX | Official Repo: Code · Weights | MIT |