microsoft/human-pose-estimation.pytorch

Health v2 · maintenance only

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3008 stars · 596 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Official PyTorch implementation of the ECCV 2018 paper 'Simple Baselines for Human Pose Estimation and Tracking' from Microsoft. It provides ResNet-based models for human keypoint detection on COCO and MPII benchmarks with pretrained weights for research.

Use cases

• detect human body keypoints in images
• estimate human pose from photos
• run 2D pose estimation on COCO dataset
• evaluate keypoint detection models on MPII
• reproduce simple baseline pose estimation results
• build pose tracking pipelines for multi-person videos

When to choose

• you need a well-tested reference implementation of the Simple Baseline pose estimation method
• you want pretrained ResNet models for COCO or MPII keypoint detection
• you are benchmarking new pose estimation ideas against a simple strong baseline

When to avoid

• you need real-time pose estimation on edge devices
• you want 3D pose estimation rather than 2D keypoints
• you need actively maintained code with recent framework support

Facets

library · maturity maintenance

computer-vision machine-learning deep-learning computer-vision image-processing deep-learning machine-learning python human-pose-estimation keypoint-detection pytorch coco mpii resnet eccv2018 pose-tracking linux gpu

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