Top 10 Video Annotation Tools

The field of artificial intelligence and machine learning is growing at an unprecedented pace and a lot of research is being conducted to build models that can accurately interpret visual data, and video annotation is one of the cornerstones of training models in this domain. The year is 2025, well, let’s discuss some of the best Video Annotation Tools that boost your project!!

What are Video Annotation tools?

A video annotation tools are the software applications that allows users to label or annotate elements of the video such as objects, actions, or events. This labeling is essential to teach machine learning models how to read images out correctly.

Why You Need Video Annotation Tools

These tools are critical to generating an annotated dataset, which in turn is used to train machine learning algorithms in many domains, such as self-driving cars, healthcare diagnostics, and security surveillance in the presence of a dynamic scene.

The Ultimate List of Top 10 Video Annotation Tools

1. Labellerr

Labellerr is a cloud-based video annotation tool to help you out with the whole annotation process. Video Format  It’s a simple interface for everyone, from beginners to pros.

Labellerr offers multiple annotation types such as Bounding boxes and polygons.

Key Features:

• It is a user-friendly UI to deal with the whole annotation process.
• Collaborative Tools: to edit simultaneously
• Automation capable: AI-powered to assist you with labeling

Pros:

• Allows multiple annotation formats
• Makes teams collaborative
• Better work performance with AI.

Cons:

• We take it as a good phase to learn the new features
• It is not public pricing.

Price: Custom pricing based on your project.

Also read: Top 10 AI Algorithms You Should Know

2. VGG Image Annotator (VIA)

VIA is developed by the Visual Geometry Group at Oxford University, and it is a versatile and open source tool for both image and video annotation. Operating in your browser directly, this is a zero-install solution for those quick annotation tasks on the go.

Key Features:

• Several Annotation Types — Boxes, polygons, etc.
• Browser-based: does not need to be installed
• As a bonus, there are Export options: JSON and CSV.

Pros:

• Free and open-source
• With a simple drag and drop interface
• Fork Start Your Own · Fork Fork: No server dependencies

Cons:

• Non-Expert collaborative features missing
• No Integrated machine learning

Price: Free!

3. Supervise.ly

Supervise.ly This is a full platform of tools for Image and video annotation. Located in the cloud, Collect provides various annotation types as well as automation to boost speed and output accuracy.

Key Features:

• Annotation Tools types: Bounding Boxes, polygons, and semantic segmentation.
• AI driven automation to complete the annotation process
• In case we want to work with others: Collaboration— you have shared projects.

Pros:

• Flexible and an annotated options.
• Automation efficiency with AI.
• Does team collaboration.

Cons:

• Small teams may need to spend a fortune on it.
• Certain features are more technical and require developer knowledge.

Price: Custom Cost based on the project;

4. Labelbox

Labelbox provides an end-to-end platform with full automation support using headless for video annotation that helps automate your labor-intensive labeling process. Featuring an easy-to-use UI, packed with top tools that scale better than ever with large datasets.

Key Features:

• Automated labeling is available with AI to minimize human intervention
• Collaboration Properties! Collaboration for Teams live.
• Management of Data: Huge data sets are efficiently handled.

Pros:

• Automation Increases efficiency
• Top level collaborative workflows
• For any size-capable project.

Cons:

• Can be too expensive for smaller one-offs
• Internet required for features on the cloud.

Price: Custom pricing available

5. CVAT (Computer Vision Annotation Tool)

A stand-alone computer vision annotation by Intel, CVAT is a freely available software to annotate both photos and videos. As this present system is all about breadth, it comes to computer vision projects like object detection and tracking.

Key Features:

• Sophisticated Annotation: Bounding Boxes, Polygons etc.
• Automation: Works well with machine learning models for automatic annotations
• Collaborative Work Area – Allows simultaneous editing of the same project by different users.

Pros:

• Open source & Free
• Feature rich for complex tasks.
• Community Active Support.

Cons:

• Installation and setup, in some cases difficult to manage with the traditional commercial utilities.
• User interface seems to fall a bit behind the commercial tools.

Price: Free.

6. Dataloop

Dataloop has a full-service data annotation platform, encompassing video. By bundling annotation tools with a data management and pipeline automation, they provide an end-to-end solution for machine learning projects.

Key Features:

• Platform in Unity: Includes annotation data management and automation
• Collaborative Tools: For projects performed as teams, it assigns roles.
• AI-Driven Automation Features: Uses AI to help with labelling

Pros:

• Single platform eliminates the need for using multiple tools.
• Automation and faster workflows.
• Can be scaled for big projects.

Cons:

• high price for a small business.
• Due to the platform being so comprehensive, the learning curve

Price: project specific quote

7. Annotorious

Annotorious is a free and open-source tool supporting both image, as well as video data annotation. It has been designed to be a light and relaxed tool, so that it can be easily installed on any workflow.

Key Features:

• Easy to use(Simple GUI): An easy to use, clean design for visual annotation.
• Integration Readiness: Can be further integrated with existing web applications.
• Multiple formats support : done with various image and video types

Pros:

• Built by engineers for engineers.
• Easy to integrate and customize.
• Resources light, depends on etc

Cons:

• Not a lot of advanced features.
• None of the built-in collaboration tools.

Price: Free.

Also read: Top 10 Data Loss Prevention Software

8. RectLabel

RectLabel is a macOS Annotation tool (for image and video data) Only. ShapeScripted created it to be a natural solution for object detection bounding box annotations.

Key Features:

• Bounding Box: Optimized to Create Object Bound Box Annotate
• Video Frame Navigation: Navigating the video frame by frame to perform precise labelling.
• Export: Compatible with the format supported in most Machine learning frameworks.

Pros:

• Mac friendly user interface
• Simplified for bounding box tasks
• Continuous updates as well as support

Cons:

• Mac only (as far as we know)
• Lacks other annotation types besides boxes

Price: Mac App Store; Pricing Different

9. Hasty.ai

It is a platform that not only helps in labeling but also befriends and learns from users’ inputs using annotation tools with machine learning capabilities, all by Hasty.ai. The method reduces the time required for manual labeling considerably.

Key Features:

• AI for assisted annotation: Uses the user inputs to automate repetitive work
• Real-Time Feedback: Instant feedback to fix your labeling.
• Collaboration: Allows team-based with shared interests

Pros:

• Uses AI to reduce manual work.
• Get better with each learning iteration.
• Contains collaborative workflows.

Cons:

• Could act as an inhibitor for smaller teams on pricing
• Needs time for the AI to take over your use-case fully.

Price: Contact for more details on availability.

10. Amazon SageMaker Ground Truth

SageMaker Ground Truth is a cloud annotation tool from Amazon that works with all kinds of annotation types — bounding boxes, polygons, and lines.

This has automation capabilities such as pre-trained models and workflows, as well as service integration with other AWS.

Key Features:

• Auto labelling with the ML models provided
• Many data formats (images, videos, text), Services other than AWS.

Pros:

• Adaptive and super fast
• Powerful infrastructure from AWS
• All-round support for use cases

Cons:

• Very complicated price model
• AWS experience

Price: Pay-as-you-go $0.50/ labeled image (dynamic)

Conclusion — Select the best Free vs. Paid Video Annotation Tools

AI and ML projects will depend on the best video annotation tool. More on the Features: There are tools above with features that cater to different types of projects, ranging from open-source tools such as CVAT and Diffogram to full-featured platforms (Labelbox, Dataloo, etc.) Not every tool will fit a project depending on the complexity of the project, needs of team collaboration, how integratable it is, and the budget. Taking the time to select the best tool means your data annotation will be better in quality and speed.