MMPose
Open-source toolbox for pose estimation and human keypoint detection built on PyTorch
Hot score
Tracking since 2026-05-16. Saturation 68%.
What is MMPose?
Based on community signals so far, MMPose is an open-source toolbox for pose estimation and human keypoint detection. It is part of the OpenMMLab ecosystem and built on PyTorch. The toolbox provides a modular framework for training, evaluating, and deploying models for 2D and 3D human pose estimation, as well as animal pose estimation. It includes a collection of state-of-the-art models, data processing tools, and evaluation metrics. MMPose aims to simplify the development and comparison of pose estimation methods, making it easier for researchers and practitioners to experiment with different architectures and datasets. The project is actively maintained on GitHub and has gained traction in the computer vision community.
Why it's trending
MMPose is trending due to its active development and adoption within the OpenMMLab ecosystem, with recent updates and community interest on GitHub.
How to use this signal
Three ways a creator, builder, or agent can put MMPose to work today. Each comes with a copy-paste prompt for ChatGPT or Claude.
Evaluate vs your current stack
Build a tutorial / demo repo
Track changelog / breaking changes
Key features
- Modular design for easy customization
- Supports 2D and 3D pose estimation
- Includes animal pose estimation models
- Pre-trained models for common datasets
- Integrated with OpenMMLab ecosystem
- Comprehensive evaluation tools
Who should use this
Researchers and developers working on human or animal pose estimation, especially those familiar with PyTorch and seeking a modular, extensible toolbox for experimentation and deployment.
Where it's surfacing
Source trail
1 source attached to this trend.
Trend velocity
plateau
Saturation
68%
Schema
Word v1
Track tomorrow's trend signals before they settle.
The daily feed, API, and MCP endpoint all read the same schema.