What is CVAT used for?

CVAT is an open-source computer vision annotation platform for labeling images, video and 3D data, with team workflows and AI-assisted labeling. It is a good fit for labeling datasets for object detection and annotation teams with review stages.

Yes. CVAT is open source under the MIT licence. Its source code is on GitHub at cvat-ai/cvat and is written mainly in Python.

Yes. CVAT is open source, so the software itself is free to use. A managed cloud version is also available, with paid plans from $33 per seat per month.

Can I self-host CVAT?

Yes. CVAT can be self-hosted on your own server or infrastructure.

What is CVAT an alternative to?

CVAT is an open-source alternative to Roboflow, Scale AI, Labelbox and SuperAnnotate. Other open-source alternatives to Roboflow include Label Studio.

Is CVAT actively maintained?

Yes. The most recent commit to CVAT was on 2 October 2026, and the latest release is v2.77.0, published on 28 September 2026. The project has 17k stars on GitHub.

CVAT: open-source alternative to Roboflow, Scale AI

About CVAT

CVAT, the Computer Vision Annotation Tool, is a platform for building labeled datasets for computer vision and other visual AI. The Community edition in this repository is the free, self-hosted open-source version, and it supports image, video and 3D annotation along with dataset management.

Teams can work together with multi-user and multi-organization support, roles, task assignments and review workflows. Users can connect their own machine learning models for detection, segmentation and tracking to speed up labeling, integrate cloud storage, and automate work through SDKs and APIs. Running it in your own infrastructure keeps data inside your environment.

The community core is MIT licensed and written mainly in Python, and it forms the base for CVAT Online, a cloud product, and CVAT Enterprise, which the company also offers alongside labeling services. Topics on the repository cover bounding boxes, semantic segmentation, object detection and tools such as TensorFlow and PyTorch.

Key features

Image, video and 3D annotation
Bounding box and segmentation labeling
AI-assisted labeling with your own models
Roles, task assignment and review workflows
Cloud storage integration
SDKs and APIs for automation

Good fit for

→Labeling datasets for object detection
→Annotation teams with review stages

Built with: Python
Tags: annotation; computer-vision; image-labeling; video-annotation; machine-learning; datasets; self-hosted; python

CVAT: questions and answers

What is CVAT used for?: CVAT is an open-source computer vision annotation platform for labeling images, video and 3D data, with team workflows and AI-assisted labeling. It is a good fit for labeling datasets for object detection and annotation teams with review stages.
Is CVAT open source?: Yes. CVAT is open source under the MIT licence. Its source code is on GitHub at cvat-ai/cvat and is written mainly in Python.
Is CVAT free?: Yes. CVAT is open source, so the software itself is free to use. A managed cloud version is also available, with paid plans from $33 per seat per month.
Can I self-host CVAT?: Yes. CVAT can be self-hosted on your own server or infrastructure.
What is CVAT an alternative to?: CVAT is an open-source alternative to Roboflow, Scale AI, Labelbox and SuperAnnotate. Other open-source alternatives to Roboflow include Label Studio.
Is CVAT actively maintained?: Yes. The most recent commit to CVAT was on 2 October 2026, and the latest release is v2.77.0, published on 28 September 2026. The project has 17k stars on GitHub.