ViTPose
A simple, accurate model for human pose estimation via keypoints. ViTPose++ handles human, animal and whole-body poses; built into the Transformers library.
- Developer
- University of Sydney and JD Explore Academy, Australia / China
- First release
- May 2022
- Latest release
- Jan 2025
- Sizes
- 33M – about 1B
- License
- Commercial use allowedApache 2.0
- Running
- On your own serverAlso runs without a GPU
- Industries
- Manufacturing and logistics, Media and production, Healthcare
What it does
- Body keypoints in photos and video
- Motion analysis in sports and rehabilitation
- Monitoring work postures and safety practices
- Preparing a skeleton for animation
Where it is used
Hardware requirements
Versions
- ViTPose / ViTPose++ в Transformers
- ViTPose++
- ViTPose
How to run it
I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems.
Frequently asked questions
Can ViTPose be used in a commercial project?
Yes. License: Apache 2.0. It allows commercial use, but it is still worth having a lawyer review the license before launch.
What hardware does ViTPose need?
At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.
Does ViTPose support Russian?
Language does not matter for this model: it does not work with text.
Where can I download ViTPose and what does it cost?
The ViTPose weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.
How I deploy it for clients
- SelectionI pick the model size for your task and hardware and test it on your examples.
- DeploymentI deploy it on your server or in a closed network and provide an API.
- Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
- IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.
Similar models
Meta's models for analyzing people in photos: pose keypoints, body part segmentation, normals and depth. Sapiens2 was trained at high resolution and adds human matting.
DetailsComputer visionYOLO (Ultralytics)Ultralytics · USACommercial use with conditionsThe most widely used real-time object detector: finds and marks items in video even on modest hardware. YOLOv5 came out back in 2020; the catalog starts from YOLOv8.
DetailsSource: huggingface.co/usyd-community/vitpose-plus-huge. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.


